Zipf0 All Model Test Data Result Combined
Result
Model Summaries
| Model |
Better than base % of the times |
| LR_10[cache_size=0.001,treshold=0.3] |
0 |
| LR_10[cache_size=0.001,treshold=0.5] |
0 |
| LR_10[cache_size=0.001,treshold=0.6] |
0 |
| LR_10[cache_size=0.001,treshold=0.7] |
0 |
| LR_10[cache_size=0.001,treshold=0.8] |
0 |
| LR_10[cache_size=0.001,treshold=0.9] |
0 |
| LR_10[cache_size=All,treshold=0.3] |
60 |
| LR_10[cache_size=All,treshold=0.5] |
52 |
| LR_10[cache_size=All,treshold=0.6] |
32 |
| LR_10[cache_size=All,treshold=0.7] |
32 |
| LR_10[cache_size=All,treshold=0.8] |
28 |
| LR_10[cache_size=All,treshold=0.9] |
4 |
| LR_11[cache_size=0.001,treshold=0.3] |
0 |
| LR_11[cache_size=0.001,treshold=0.5] |
0 |
| LR_11[cache_size=0.001,treshold=0.6] |
0 |
| LR_11[cache_size=0.001,treshold=0.7] |
0 |
| LR_11[cache_size=0.001,treshold=0.8] |
0 |
| LR_11[cache_size=0.001,treshold=0.9] |
0 |
| LR_11[cache_size=All,treshold=0.3] |
60 |
| LR_11[cache_size=All,treshold=0.5] |
48 |
| LR_11[cache_size=All,treshold=0.6] |
32 |
| LR_11[cache_size=All,treshold=0.7] |
36 |
| LR_11[cache_size=All,treshold=0.8] |
28 |
| LR_11[cache_size=All,treshold=0.9] |
4 |
| LR_12[cache_size=0.001,treshold=0.3] |
0 |
| LR_12[cache_size=0.001,treshold=0.5] |
0 |
| LR_12[cache_size=0.001,treshold=0.6] |
0 |
| LR_12[cache_size=0.001,treshold=0.7] |
0 |
| LR_12[cache_size=0.001,treshold=0.8] |
0 |
| LR_12[cache_size=0.001,treshold=0.9] |
0 |
| LR_12[cache_size=All,treshold=0.3] |
64 |
| LR_12[cache_size=All,treshold=0.5] |
48 |
| LR_12[cache_size=All,treshold=0.6] |
32 |
| LR_12[cache_size=All,treshold=0.7] |
36 |
| LR_12[cache_size=All,treshold=0.8] |
32 |
| LR_12[cache_size=All,treshold=0.9] |
4 |
| LR_13[cache_size=0.001,treshold=0.3] |
0 |
| LR_13[cache_size=0.001,treshold=0.5] |
0 |
| LR_13[cache_size=0.001,treshold=0.6] |
0 |
| LR_13[cache_size=0.001,treshold=0.7] |
0 |
| LR_13[cache_size=0.001,treshold=0.8] |
0 |
| LR_13[cache_size=0.001,treshold=0.9] |
0 |
| LR_13[cache_size=All,treshold=0.3] |
60 |
| LR_13[cache_size=All,treshold=0.5] |
28 |
| LR_13[cache_size=All,treshold=0.6] |
16 |
| LR_13[cache_size=All,treshold=0.7] |
0 |
| LR_13[cache_size=All,treshold=0.8] |
0 |
| LR_13[cache_size=All,treshold=0.9] |
0 |
| LR_14[cache_size=0.001,treshold=0.3] |
0 |
| LR_14[cache_size=0.001,treshold=0.5] |
0 |
| LR_14[cache_size=0.001,treshold=0.6] |
0 |
| LR_14[cache_size=0.001,treshold=0.7] |
0 |
| LR_14[cache_size=0.001,treshold=0.8] |
0 |
| LR_14[cache_size=0.001,treshold=0.9] |
0 |
| LR_14[cache_size=All,treshold=0.3] |
60 |
| LR_14[cache_size=All,treshold=0.5] |
28 |
| LR_14[cache_size=All,treshold=0.6] |
16 |
| LR_14[cache_size=All,treshold=0.7] |
0 |
| LR_14[cache_size=All,treshold=0.8] |
0 |
| LR_14[cache_size=All,treshold=0.9] |
0 |
| LR_15[cache_size=0.001,treshold=0.3] |
0 |
| LR_15[cache_size=0.001,treshold=0.5] |
0 |
| LR_15[cache_size=0.001,treshold=0.6] |
0 |
| LR_15[cache_size=0.001,treshold=0.7] |
0 |
| LR_15[cache_size=0.001,treshold=0.8] |
0 |
| LR_15[cache_size=0.001,treshold=0.9] |
0 |
| LR_15[cache_size=All,treshold=0.3] |
60 |
| LR_15[cache_size=All,treshold=0.5] |
28 |
| LR_15[cache_size=All,treshold=0.6] |
16 |
| LR_15[cache_size=All,treshold=0.7] |
0 |
| LR_15[cache_size=All,treshold=0.8] |
0 |
| LR_15[cache_size=All,treshold=0.9] |
0 |
| LR_1[cache_size=0.001,treshold=0.5] |
0 |
| LR_1[cache_size=All,treshold=0.5] |
52 |
| LR_1_log[cache_size=0.001,treshold=0.5] |
0 |
| LR_1_log[cache_size=All,treshold=0.5] |
52 |
| LR_1_mean[cache_size=0.001,treshold=0.5] |
0 |
| LR_1_mean[cache_size=All,treshold=0.5] |
24 |
| LR_1_robust_scaler[cache_size=0.001,treshold=0.5] |
0 |
| LR_1_robust_scaler[cache_size=All,treshold=0.5] |
44 |
| LR_1_std_scaler[cache_size=0.001,treshold=0.5] |
0 |
| LR_1_std_scaler[cache_size=All,treshold=0.5] |
44 |
| LR_2[cache_size=0.001,treshold=0.5] |
0 |
| LR_2[cache_size=All,treshold=0.5] |
52 |
| LR_2_log[cache_size=0.001,treshold=0.5] |
0 |
| LR_2_log[cache_size=All,treshold=0.5] |
52 |
| LR_2_mean[cache_size=0.001,treshold=0.5] |
0 |
| LR_2_mean[cache_size=All,treshold=0.5] |
32 |
| LR_3[cache_size=0.001,treshold=0.5] |
0 |
| LR_3[cache_size=All,treshold=0.5] |
52 |
| LR_3_log[cache_size=0.001,treshold=0.5] |
0 |
| LR_3_log[cache_size=All,treshold=0.5] |
52 |
| LR_3_mean[cache_size=0.001,treshold=0.5] |
0 |
| LR_3_mean[cache_size=All,treshold=0.5] |
28 |
| LR_4[cache_size=0.001,treshold=0.5] |
0 |
| LR_4[cache_size=All,treshold=0.5] |
60 |
| LR_4_log[cache_size=0.001,treshold=0.5] |
0 |
| LR_4_log[cache_size=All,treshold=0.5] |
60 |
| LR_4_mean[cache_size=0.001,treshold=0.5] |
0 |
| LR_4_mean[cache_size=All,treshold=0.5] |
56 |
| LR_4_robust_scaler[cache_size=0.001,treshold=0.5] |
0 |
| LR_4_robust_scaler[cache_size=All,treshold=0.5] |
56 |
| LR_4_std_scaler[cache_size=0.001,treshold=0.5] |
0 |
| LR_4_std_scaler[cache_size=All,treshold=0.5] |
56 |
| LR_5[cache_size=0.001,treshold=0.5] |
0 |
| LR_5[cache_size=All,treshold=0.5] |
56 |
| LR_5_imba[cache_size=0.001,treshold=0.5] |
0 |
| LR_5_imba[cache_size=All,treshold=0.5] |
60 |
| LR_6[cache_size=0.001,treshold=0.5] |
0 |
| LR_6[cache_size=All,treshold=0.5] |
56 |
| LR_6_imba[cache_size=0.001,treshold=0.5] |
0 |
| LR_6_imba[cache_size=All,treshold=0.5] |
60 |
| LR_7[cache_size=0.001,treshold=0.3] |
0 |
| LR_7[cache_size=0.001,treshold=0.5] |
0 |
| LR_7[cache_size=0.001,treshold=0.6] |
0 |
| LR_7[cache_size=0.001,treshold=0.7] |
0 |
| LR_7[cache_size=0.001,treshold=0.8] |
0 |
| LR_7[cache_size=0.001,treshold=0.9] |
0 |
| LR_7[cache_size=All,treshold=0.3] |
60 |
| LR_7[cache_size=All,treshold=0.5] |
52 |
| LR_7[cache_size=All,treshold=0.6] |
48 |
| LR_7[cache_size=All,treshold=0.7] |
36 |
| LR_7[cache_size=All,treshold=0.8] |
44 |
| LR_7[cache_size=All,treshold=0.9] |
16 |
| LR_8[cache_size=0.001,treshold=0.3] |
0 |
| LR_8[cache_size=0.001,treshold=0.5] |
0 |
| LR_8[cache_size=0.001,treshold=0.6] |
0 |
| LR_8[cache_size=0.001,treshold=0.7] |
0 |
| LR_8[cache_size=0.001,treshold=0.8] |
0 |
| LR_8[cache_size=0.001,treshold=0.9] |
0 |
| LR_8[cache_size=All,treshold=0.3] |
60 |
| LR_8[cache_size=All,treshold=0.5] |
52 |
| LR_8[cache_size=All,treshold=0.6] |
36 |
| LR_8[cache_size=All,treshold=0.7] |
36 |
| LR_8[cache_size=All,treshold=0.8] |
40 |
| LR_8[cache_size=All,treshold=0.9] |
12 |
| LR_9[cache_size=0.001,treshold=0.3] |
0 |
| LR_9[cache_size=0.001,treshold=0.5] |
0 |
| LR_9[cache_size=0.001,treshold=0.6] |
0 |
| LR_9[cache_size=0.001,treshold=0.7] |
0 |
| LR_9[cache_size=0.001,treshold=0.8] |
0 |
| LR_9[cache_size=0.001,treshold=0.9] |
0 |
| LR_9[cache_size=All,treshold=0.3] |
60 |
| LR_9[cache_size=All,treshold=0.5] |
52 |
| LR_9[cache_size=All,treshold=0.6] |
44 |
| LR_9[cache_size=All,treshold=0.7] |
36 |
| LR_9[cache_size=All,treshold=0.8] |
40 |
| LR_9[cache_size=All,treshold=0.9] |
16 |
| LR_10[cache_size=0.01,treshold=0.3] |
80 |
| LR_10[cache_size=0.01,treshold=0.5] |
80 |
| LR_10[cache_size=0.01,treshold=0.6] |
80 |
| LR_10[cache_size=0.01,treshold=0.7] |
0 |
| LR_10[cache_size=0.01,treshold=0.8] |
0 |
| LR_10[cache_size=0.01,treshold=0.9] |
0 |
| LR_11[cache_size=0.01,treshold=0.3] |
80 |
| LR_11[cache_size=0.01,treshold=0.5] |
60 |
| LR_11[cache_size=0.01,treshold=0.6] |
60 |
| LR_11[cache_size=0.01,treshold=0.7] |
40 |
| LR_11[cache_size=0.01,treshold=0.8] |
0 |
| LR_11[cache_size=0.01,treshold=0.9] |
0 |
| LR_12[cache_size=0.01,treshold=0.3] |
80 |
| LR_12[cache_size=0.01,treshold=0.5] |
60 |
| LR_12[cache_size=0.01,treshold=0.6] |
60 |
| LR_12[cache_size=0.01,treshold=0.7] |
40 |
| LR_12[cache_size=0.01,treshold=0.8] |
0 |
| LR_12[cache_size=0.01,treshold=0.9] |
0 |
| LR_13[cache_size=0.01,treshold=0.3] |
80 |
| LR_13[cache_size=0.01,treshold=0.5] |
80 |
| LR_13[cache_size=0.01,treshold=0.6] |
80 |
| LR_13[cache_size=0.01,treshold=0.7] |
0 |
| LR_13[cache_size=0.01,treshold=0.8] |
0 |
| LR_13[cache_size=0.01,treshold=0.9] |
0 |
| LR_14[cache_size=0.01,treshold=0.3] |
80 |
| LR_14[cache_size=0.01,treshold=0.5] |
60 |
| LR_14[cache_size=0.01,treshold=0.6] |
60 |
| LR_14[cache_size=0.01,treshold=0.7] |
80 |
| LR_14[cache_size=0.01,treshold=0.8] |
0 |
| LR_14[cache_size=0.01,treshold=0.9] |
0 |
| LR_15[cache_size=0.01,treshold=0.3] |
80 |
| LR_15[cache_size=0.01,treshold=0.5] |
60 |
| LR_15[cache_size=0.01,treshold=0.6] |
60 |
| LR_15[cache_size=0.01,treshold=0.7] |
80 |
| LR_15[cache_size=0.01,treshold=0.8] |
0 |
| LR_15[cache_size=0.01,treshold=0.9] |
0 |
| LR_1[cache_size=0.01,treshold=0.5] |
60 |
| LR_1_log[cache_size=0.01,treshold=0.5] |
80 |
| LR_1_mean[cache_size=0.01,treshold=0.5] |
80 |
| LR_1_robust_scaler[cache_size=0.01,treshold=0.5] |
60 |
| LR_1_std_scaler[cache_size=0.01,treshold=0.5] |
60 |
| LR_2[cache_size=0.01,treshold=0.5] |
60 |
| LR_2_log[cache_size=0.01,treshold=0.5] |
80 |
| LR_2_mean[cache_size=0.01,treshold=0.5] |
80 |
| LR_3[cache_size=0.01,treshold=0.5] |
80 |
| LR_3_log[cache_size=0.01,treshold=0.5] |
80 |
| LR_3_mean[cache_size=0.01,treshold=0.5] |
80 |
| LR_4[cache_size=0.01,treshold=0.5] |
60 |
| LR_4_log[cache_size=0.01,treshold=0.5] |
80 |
| LR_4_mean[cache_size=0.01,treshold=0.5] |
80 |
| LR_4_robust_scaler[cache_size=0.01,treshold=0.5] |
60 |
| LR_4_std_scaler[cache_size=0.01,treshold=0.5] |
60 |
| LR_5[cache_size=0.01,treshold=0.5] |
60 |
| LR_5_imba[cache_size=0.01,treshold=0.5] |
80 |
| LR_6[cache_size=0.01,treshold=0.5] |
80 |
| LR_6_imba[cache_size=0.01,treshold=0.5] |
80 |
| LR_7[cache_size=0.01,treshold=0.3] |
80 |
| LR_7[cache_size=0.01,treshold=0.5] |
80 |
| LR_7[cache_size=0.01,treshold=0.6] |
80 |
| LR_7[cache_size=0.01,treshold=0.7] |
0 |
| LR_7[cache_size=0.01,treshold=0.8] |
0 |
| LR_7[cache_size=0.01,treshold=0.9] |
0 |
| LR_8[cache_size=0.01,treshold=0.3] |
80 |
| LR_8[cache_size=0.01,treshold=0.5] |
80 |
| LR_8[cache_size=0.01,treshold=0.6] |
60 |
| LR_8[cache_size=0.01,treshold=0.7] |
60 |
| LR_8[cache_size=0.01,treshold=0.8] |
0 |
| LR_8[cache_size=0.01,treshold=0.9] |
0 |
| LR_9[cache_size=0.01,treshold=0.3] |
80 |
| LR_9[cache_size=0.01,treshold=0.5] |
80 |
| LR_9[cache_size=0.01,treshold=0.6] |
80 |
| LR_9[cache_size=0.01,treshold=0.7] |
60 |
| LR_9[cache_size=0.01,treshold=0.8] |
0 |
| LR_9[cache_size=0.01,treshold=0.9] |
0 |
| LR_10[cache_size=0.1,treshold=0.3] |
80 |
| LR_10[cache_size=0.1,treshold=0.5] |
60 |
| LR_10[cache_size=0.1,treshold=0.6] |
60 |
| LR_10[cache_size=0.1,treshold=0.7] |
60 |
| LR_10[cache_size=0.1,treshold=0.8] |
40 |
| LR_10[cache_size=0.1,treshold=0.9] |
20 |
| LR_11[cache_size=0.1,treshold=0.3] |
80 |
| LR_11[cache_size=0.1,treshold=0.5] |
60 |
| LR_11[cache_size=0.1,treshold=0.6] |
60 |
| LR_11[cache_size=0.1,treshold=0.7] |
60 |
| LR_11[cache_size=0.1,treshold=0.8] |
40 |
| LR_11[cache_size=0.1,treshold=0.9] |
20 |
| LR_12[cache_size=0.1,treshold=0.3] |
80 |
| LR_12[cache_size=0.1,treshold=0.5] |
60 |
| LR_12[cache_size=0.1,treshold=0.6] |
40 |
| LR_12[cache_size=0.1,treshold=0.7] |
40 |
| LR_12[cache_size=0.1,treshold=0.8] |
20 |
| LR_12[cache_size=0.1,treshold=0.9] |
20 |
| LR_13[cache_size=0.1,treshold=0.3] |
80 |
| LR_13[cache_size=0.1,treshold=0.5] |
60 |
| LR_13[cache_size=0.1,treshold=0.6] |
80 |
| LR_13[cache_size=0.1,treshold=0.7] |
40 |
| LR_13[cache_size=0.1,treshold=0.8] |
0 |
| LR_13[cache_size=0.1,treshold=0.9] |
0 |
| LR_14[cache_size=0.1,treshold=0.3] |
80 |
| LR_14[cache_size=0.1,treshold=0.5] |
60 |
| LR_14[cache_size=0.1,treshold=0.6] |
60 |
| LR_14[cache_size=0.1,treshold=0.7] |
60 |
| LR_14[cache_size=0.1,treshold=0.8] |
0 |
| LR_14[cache_size=0.1,treshold=0.9] |
0 |
| LR_15[cache_size=0.1,treshold=0.3] |
80 |
| LR_15[cache_size=0.1,treshold=0.5] |
60 |
| LR_15[cache_size=0.1,treshold=0.6] |
60 |
| LR_15[cache_size=0.1,treshold=0.7] |
60 |
| LR_15[cache_size=0.1,treshold=0.8] |
0 |
| LR_15[cache_size=0.1,treshold=0.9] |
0 |
| LR_1[cache_size=0.1,treshold=0.5] |
80 |
| LR_1_log[cache_size=0.1,treshold=0.5] |
80 |
| LR_1_mean[cache_size=0.1,treshold=0.5] |
80 |
| LR_1_robust_scaler[cache_size=0.1,treshold=0.5] |
80 |
| LR_1_std_scaler[cache_size=0.1,treshold=0.5] |
80 |
| LR_2[cache_size=0.1,treshold=0.5] |
80 |
| LR_2_log[cache_size=0.1,treshold=0.5] |
80 |
| LR_2_mean[cache_size=0.1,treshold=0.5] |
80 |
| LR_3[cache_size=0.1,treshold=0.5] |
80 |
| LR_3_log[cache_size=0.1,treshold=0.5] |
80 |
| LR_3_mean[cache_size=0.1,treshold=0.5] |
80 |
| LR_4[cache_size=0.1,treshold=0.5] |
80 |
| LR_4_log[cache_size=0.1,treshold=0.5] |
60 |
| LR_4_mean[cache_size=0.1,treshold=0.5] |
60 |
| LR_4_robust_scaler[cache_size=0.1,treshold=0.5] |
80 |
| LR_4_std_scaler[cache_size=0.1,treshold=0.5] |
80 |
| LR_5[cache_size=0.1,treshold=0.5] |
80 |
| LR_5_imba[cache_size=0.1,treshold=0.5] |
80 |
| LR_6[cache_size=0.1,treshold=0.5] |
80 |
| LR_6_imba[cache_size=0.1,treshold=0.5] |
80 |
| LR_7[cache_size=0.1,treshold=0.3] |
80 |
| LR_7[cache_size=0.1,treshold=0.5] |
80 |
| LR_7[cache_size=0.1,treshold=0.6] |
40 |
| LR_7[cache_size=0.1,treshold=0.7] |
60 |
| LR_7[cache_size=0.1,treshold=0.8] |
0 |
| LR_7[cache_size=0.1,treshold=0.9] |
0 |
| LR_8[cache_size=0.1,treshold=0.3] |
80 |
| LR_8[cache_size=0.1,treshold=0.5] |
80 |
| LR_8[cache_size=0.1,treshold=0.6] |
80 |
| LR_8[cache_size=0.1,treshold=0.7] |
60 |
| LR_8[cache_size=0.1,treshold=0.8] |
0 |
| LR_8[cache_size=0.1,treshold=0.9] |
0 |
| LR_9[cache_size=0.1,treshold=0.3] |
80 |
| LR_9[cache_size=0.1,treshold=0.5] |
80 |
| LR_9[cache_size=0.1,treshold=0.6] |
80 |
| LR_9[cache_size=0.1,treshold=0.7] |
40 |
| LR_9[cache_size=0.1,treshold=0.8] |
0 |
| LR_9[cache_size=0.1,treshold=0.9] |
0 |
| LR_10[cache_size=0.2,treshold=0.3] |
40 |
| LR_10[cache_size=0.2,treshold=0.5] |
60 |
| LR_10[cache_size=0.2,treshold=0.6] |
60 |
| LR_10[cache_size=0.2,treshold=0.7] |
60 |
| LR_10[cache_size=0.2,treshold=0.8] |
0 |
| LR_10[cache_size=0.2,treshold=0.9] |
0 |
| LR_11[cache_size=0.2,treshold=0.3] |
40 |
| LR_11[cache_size=0.2,treshold=0.5] |
60 |
| LR_11[cache_size=0.2,treshold=0.6] |
60 |
| LR_11[cache_size=0.2,treshold=0.7] |
60 |
| LR_11[cache_size=0.2,treshold=0.8] |
0 |
| LR_11[cache_size=0.2,treshold=0.9] |
0 |
| LR_12[cache_size=0.2,treshold=0.3] |
40 |
| LR_12[cache_size=0.2,treshold=0.5] |
60 |
| LR_12[cache_size=0.2,treshold=0.6] |
60 |
| LR_12[cache_size=0.2,treshold=0.7] |
60 |
| LR_12[cache_size=0.2,treshold=0.8] |
0 |
| LR_12[cache_size=0.2,treshold=0.9] |
0 |
| LR_13[cache_size=0.2,treshold=0.3] |
40 |
| LR_13[cache_size=0.2,treshold=0.5] |
40 |
| LR_13[cache_size=0.2,treshold=0.6] |
40 |
| LR_13[cache_size=0.2,treshold=0.7] |
60 |
| LR_13[cache_size=0.2,treshold=0.8] |
0 |
| LR_13[cache_size=0.2,treshold=0.9] |
0 |
| LR_14[cache_size=0.2,treshold=0.3] |
40 |
| LR_14[cache_size=0.2,treshold=0.5] |
40 |
| LR_14[cache_size=0.2,treshold=0.6] |
40 |
| LR_14[cache_size=0.2,treshold=0.7] |
60 |
| LR_14[cache_size=0.2,treshold=0.8] |
0 |
| LR_14[cache_size=0.2,treshold=0.9] |
0 |
| LR_15[cache_size=0.2,treshold=0.3] |
60 |
| LR_15[cache_size=0.2,treshold=0.5] |
40 |
| LR_15[cache_size=0.2,treshold=0.6] |
40 |
| LR_15[cache_size=0.2,treshold=0.7] |
40 |
| LR_15[cache_size=0.2,treshold=0.8] |
0 |
| LR_15[cache_size=0.2,treshold=0.9] |
0 |
| LR_1[cache_size=0.2,treshold=0.5] |
40 |
| LR_1_log[cache_size=0.2,treshold=0.5] |
40 |
| LR_1_mean[cache_size=0.2,treshold=0.5] |
40 |
| LR_1_robust_scaler[cache_size=0.2,treshold=0.5] |
40 |
| LR_1_std_scaler[cache_size=0.2,treshold=0.5] |
40 |
| LR_2[cache_size=0.2,treshold=0.5] |
40 |
| LR_2_log[cache_size=0.2,treshold=0.5] |
40 |
| LR_2_mean[cache_size=0.2,treshold=0.5] |
40 |
| LR_3[cache_size=0.2,treshold=0.5] |
40 |
| LR_3_log[cache_size=0.2,treshold=0.5] |
40 |
| LR_3_mean[cache_size=0.2,treshold=0.5] |
40 |
| LR_4[cache_size=0.2,treshold=0.5] |
40 |
| LR_4_log[cache_size=0.2,treshold=0.5] |
40 |
| LR_4_mean[cache_size=0.2,treshold=0.5] |
40 |
| LR_4_robust_scaler[cache_size=0.2,treshold=0.5] |
40 |
| LR_4_std_scaler[cache_size=0.2,treshold=0.5] |
40 |
| LR_5[cache_size=0.2,treshold=0.5] |
40 |
| LR_5_imba[cache_size=0.2,treshold=0.5] |
60 |
| LR_6[cache_size=0.2,treshold=0.5] |
40 |
| LR_6_imba[cache_size=0.2,treshold=0.5] |
60 |
| LR_7[cache_size=0.2,treshold=0.3] |
40 |
| LR_7[cache_size=0.2,treshold=0.5] |
40 |
| LR_7[cache_size=0.2,treshold=0.6] |
60 |
| LR_7[cache_size=0.2,treshold=0.7] |
60 |
| LR_7[cache_size=0.2,treshold=0.8] |
0 |
| LR_7[cache_size=0.2,treshold=0.9] |
0 |
| LR_8[cache_size=0.2,treshold=0.3] |
60 |
| LR_8[cache_size=0.2,treshold=0.5] |
40 |
| LR_8[cache_size=0.2,treshold=0.6] |
60 |
| LR_8[cache_size=0.2,treshold=0.7] |
60 |
| LR_8[cache_size=0.2,treshold=0.8] |
0 |
| LR_8[cache_size=0.2,treshold=0.9] |
0 |
| LR_9[cache_size=0.2,treshold=0.3] |
60 |
| LR_9[cache_size=0.2,treshold=0.5] |
40 |
| LR_9[cache_size=0.2,treshold=0.6] |
60 |
| LR_9[cache_size=0.2,treshold=0.7] |
60 |
| LR_9[cache_size=0.2,treshold=0.8] |
0 |
| LR_9[cache_size=0.2,treshold=0.9] |
0 |
| LR_10[cache_size=0.4,treshold=0.3] |
60 |
| LR_10[cache_size=0.4,treshold=0.5] |
80 |
| LR_10[cache_size=0.4,treshold=0.6] |
80 |
| LR_10[cache_size=0.4,treshold=0.7] |
40 |
| LR_10[cache_size=0.4,treshold=0.8] |
40 |
| LR_10[cache_size=0.4,treshold=0.9] |
20 |
| LR_11[cache_size=0.4,treshold=0.3] |
60 |
| LR_11[cache_size=0.4,treshold=0.5] |
80 |
| LR_11[cache_size=0.4,treshold=0.6] |
60 |
| LR_11[cache_size=0.4,treshold=0.7] |
40 |
| LR_11[cache_size=0.4,treshold=0.8] |
0 |
| LR_11[cache_size=0.4,treshold=0.9] |
0 |
| LR_12[cache_size=0.4,treshold=0.3] |
80 |
| LR_12[cache_size=0.4,treshold=0.5] |
80 |
| LR_12[cache_size=0.4,treshold=0.6] |
80 |
| LR_12[cache_size=0.4,treshold=0.7] |
40 |
| LR_12[cache_size=0.4,treshold=0.8] |
0 |
| LR_12[cache_size=0.4,treshold=0.9] |
0 |
| LR_13[cache_size=0.4,treshold=0.3] |
60 |
| LR_13[cache_size=0.4,treshold=0.5] |
80 |
| LR_13[cache_size=0.4,treshold=0.6] |
80 |
| LR_13[cache_size=0.4,treshold=0.7] |
40 |
| LR_13[cache_size=0.4,treshold=0.8] |
20 |
| LR_13[cache_size=0.4,treshold=0.9] |
20 |
| LR_14[cache_size=0.4,treshold=0.3] |
60 |
| LR_14[cache_size=0.4,treshold=0.5] |
80 |
| LR_14[cache_size=0.4,treshold=0.6] |
80 |
| LR_14[cache_size=0.4,treshold=0.7] |
40 |
| LR_14[cache_size=0.4,treshold=0.8] |
20 |
| LR_14[cache_size=0.4,treshold=0.9] |
20 |
| LR_15[cache_size=0.4,treshold=0.3] |
80 |
| LR_15[cache_size=0.4,treshold=0.5] |
80 |
| LR_15[cache_size=0.4,treshold=0.6] |
80 |
| LR_15[cache_size=0.4,treshold=0.7] |
40 |
| LR_15[cache_size=0.4,treshold=0.8] |
20 |
| LR_15[cache_size=0.4,treshold=0.9] |
20 |
| LR_1[cache_size=0.4,treshold=0.5] |
60 |
| LR_1_log[cache_size=0.4,treshold=0.5] |
80 |
| LR_1_mean[cache_size=0.4,treshold=0.5] |
80 |
| LR_1_robust_scaler[cache_size=0.4,treshold=0.5] |
60 |
| LR_1_std_scaler[cache_size=0.4,treshold=0.5] |
60 |
| LR_2[cache_size=0.4,treshold=0.5] |
60 |
| LR_2_log[cache_size=0.4,treshold=0.5] |
80 |
| LR_2_mean[cache_size=0.4,treshold=0.5] |
80 |
| LR_3[cache_size=0.4,treshold=0.5] |
60 |
| LR_3_log[cache_size=0.4,treshold=0.5] |
80 |
| LR_3_mean[cache_size=0.4,treshold=0.5] |
80 |
| LR_4[cache_size=0.4,treshold=0.5] |
80 |
| LR_4_log[cache_size=0.4,treshold=0.5] |
60 |
| LR_4_mean[cache_size=0.4,treshold=0.5] |
80 |
| LR_4_robust_scaler[cache_size=0.4,treshold=0.5] |
80 |
| LR_4_std_scaler[cache_size=0.4,treshold=0.5] |
80 |
| LR_5[cache_size=0.4,treshold=0.5] |
80 |
| LR_5_imba[cache_size=0.4,treshold=0.5] |
80 |
| LR_6[cache_size=0.4,treshold=0.5] |
80 |
| LR_6_imba[cache_size=0.4,treshold=0.5] |
80 |
| LR_7[cache_size=0.4,treshold=0.3] |
80 |
| LR_7[cache_size=0.4,treshold=0.5] |
80 |
| LR_7[cache_size=0.4,treshold=0.6] |
80 |
| LR_7[cache_size=0.4,treshold=0.7] |
40 |
| LR_7[cache_size=0.4,treshold=0.8] |
20 |
| LR_7[cache_size=0.4,treshold=0.9] |
40 |
| LR_8[cache_size=0.4,treshold=0.3] |
80 |
| LR_8[cache_size=0.4,treshold=0.5] |
80 |
| LR_8[cache_size=0.4,treshold=0.6] |
80 |
| LR_8[cache_size=0.4,treshold=0.7] |
20 |
| LR_8[cache_size=0.4,treshold=0.8] |
0 |
| LR_8[cache_size=0.4,treshold=0.9] |
0 |
| LR_9[cache_size=0.4,treshold=0.3] |
80 |
| LR_9[cache_size=0.4,treshold=0.5] |
80 |
| LR_9[cache_size=0.4,treshold=0.6] |
80 |
| LR_9[cache_size=0.4,treshold=0.7] |
20 |
| LR_9[cache_size=0.4,treshold=0.8] |
0 |
| LR_9[cache_size=0.4,treshold=0.9] |
0 |
| Offline Clock 1st iteration |
0 |
| Offline Clock 2nd iteration |
100 |
| Zipf Optimal Distribution |
56 |
| Model |
Max |
Min |
Avg |
Mdn |
| LR_10[cache_size=0.001,treshold=0.3] |
97.5251 |
97.4386 |
97.476 |
97.4733 |
| LR_10[cache_size=0.001,treshold=0.5] |
93.7553 |
93.6115 |
93.6695 |
93.6449 |
| LR_10[cache_size=0.001,treshold=0.6] |
87.3734 |
87.1943 |
87.2682 |
87.2438 |
| LR_10[cache_size=0.001,treshold=0.7] |
26.0166 |
25.6524 |
25.8338 |
25.8229 |
| LR_10[cache_size=0.001,treshold=0.8] |
1.66789 |
1.61523 |
1.6328 |
1.62872 |
| LR_10[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=All,treshold=0.3] |
98.0623 |
90.7947 |
95.1189 |
95.4773 |
| LR_10[cache_size=All,treshold=0.5] |
86.4887 |
13.4401 |
46.6968 |
52.599 |
| LR_10[cache_size=All,treshold=0.6] |
76.5894 |
0.700736 |
28.9161 |
16.4192 |
| LR_10[cache_size=All,treshold=0.7] |
58.9215 |
0.223497 |
15.3703 |
6.63903 |
| LR_10[cache_size=All,treshold=0.8] |
18.1337 |
0.0247083 |
5.37182 |
4.12296 |
| LR_10[cache_size=All,treshold=0.9] |
3.45624 |
0.00273211 |
1.52489 |
1.60022 |
| LR_11[cache_size=0.001,treshold=0.3] |
91.9068 |
91.6789 |
91.737 |
91.6959 |
| LR_11[cache_size=0.001,treshold=0.5] |
75.224 |
75.0761 |
75.1469 |
75.1551 |
| LR_11[cache_size=0.001,treshold=0.6] |
58.7067 |
58.5526 |
58.6333 |
58.6431 |
| LR_11[cache_size=0.001,treshold=0.7] |
26.8304 |
26.4186 |
26.6328 |
26.6834 |
| LR_11[cache_size=0.001,treshold=0.8] |
0.0351018 |
0.0159226 |
0.0242171 |
0.0229968 |
| LR_11[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=All,treshold=0.3] |
98.119 |
70.9173 |
90.6142 |
94.2833 |
| LR_11[cache_size=All,treshold=0.5] |
85.2065 |
14.0347 |
41.6486 |
28.5799 |
| LR_11[cache_size=All,treshold=0.6] |
76.3445 |
0.726802 |
26.714 |
9.63783 |
| LR_11[cache_size=All,treshold=0.7] |
59.9017 |
0.241822 |
14.6793 |
3.7238 |
| LR_11[cache_size=All,treshold=0.8] |
23.2517 |
0.0280467 |
5.98543 |
2.12261 |
| LR_11[cache_size=All,treshold=0.9] |
3.5706 |
0.00303224 |
1.38632 |
0.809615 |
| LR_12[cache_size=0.001,treshold=0.3] |
96.3863 |
96.2251 |
96.285 |
96.2771 |
| LR_12[cache_size=0.001,treshold=0.5] |
85.2348 |
85.0491 |
85.1357 |
85.1452 |
| LR_12[cache_size=0.001,treshold=0.6] |
71.7157 |
71.628 |
71.6869 |
71.6919 |
| LR_12[cache_size=0.001,treshold=0.7] |
43.0577 |
42.8483 |
42.9785 |
42.9977 |
| LR_12[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=All,treshold=0.3] |
98.1894 |
58.5912 |
87.9937 |
93.9287 |
| LR_12[cache_size=All,treshold=0.5] |
84.2409 |
14.4434 |
39.4358 |
18.1608 |
| LR_12[cache_size=All,treshold=0.6] |
75.5171 |
0.732406 |
26.1776 |
9.67854 |
| LR_12[cache_size=All,treshold=0.7] |
59.6489 |
0.244398 |
14.1821 |
2.88019 |
| LR_12[cache_size=All,treshold=0.8] |
22.6008 |
0.0280312 |
5.76445 |
1.64825 |
| LR_12[cache_size=All,treshold=0.9] |
3.53358 |
0.00298583 |
1.32528 |
0.557424 |
| LR_13[cache_size=0.001,treshold=0.3] |
97.5371 |
97.4516 |
97.4848 |
97.4754 |
| LR_13[cache_size=0.001,treshold=0.5] |
93.7102 |
93.5653 |
93.6261 |
93.6148 |
| LR_13[cache_size=0.001,treshold=0.6] |
87.3296 |
87.1502 |
87.2206 |
87.1728 |
| LR_13[cache_size=0.001,treshold=0.7] |
26.0862 |
25.7144 |
25.8855 |
25.879 |
| LR_13[cache_size=0.001,treshold=0.8] |
1.646 |
1.56919 |
1.60719 |
1.60666 |
| LR_13[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=All,treshold=0.3] |
98.4936 |
81.7862 |
90.8247 |
92.2814 |
| LR_13[cache_size=All,treshold=0.5] |
76.5658 |
0.0120017 |
25.3015 |
4.51844 |
| LR_13[cache_size=All,treshold=0.6] |
42.0709 |
0.00108558 |
8.72344 |
0.470934 |
| LR_13[cache_size=All,treshold=0.7] |
1.00954 |
-5.53978e-06 |
0.221484 |
2.10371e-05 |
| LR_13[cache_size=All,treshold=0.8] |
0.995569 |
0 |
0.216238 |
0 |
| LR_13[cache_size=All,treshold=0.9] |
0.986525 |
0 |
0.214378 |
0 |
| LR_14[cache_size=0.001,treshold=0.3] |
91.9068 |
91.6789 |
91.737 |
91.6959 |
| LR_14[cache_size=0.001,treshold=0.5] |
75.224 |
75.0761 |
75.1469 |
75.1551 |
| LR_14[cache_size=0.001,treshold=0.6] |
58.7067 |
58.5526 |
58.6331 |
58.6431 |
| LR_14[cache_size=0.001,treshold=0.7] |
27.3288 |
26.9986 |
27.1804 |
27.238 |
| LR_14[cache_size=0.001,treshold=0.8] |
0.0280814 |
0.011942 |
0.0174121 |
0.0159978 |
| LR_14[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=All,treshold=0.3] |
98.5848 |
67.9597 |
87.5698 |
92.7413 |
| LR_14[cache_size=All,treshold=0.5] |
76.5447 |
0.014624 |
25.5286 |
6.62513 |
| LR_14[cache_size=All,treshold=0.6] |
41.8591 |
0.0015179 |
8.65122 |
0.28922 |
| LR_14[cache_size=All,treshold=0.7] |
1.01971 |
0 |
0.221567 |
3.15585e-05 |
| LR_14[cache_size=All,treshold=0.8] |
0.996072 |
0 |
0.21626 |
0 |
| LR_14[cache_size=All,treshold=0.9] |
0.98964 |
0 |
0.214784 |
0 |
| LR_15[cache_size=0.001,treshold=0.3] |
96.3873 |
96.2321 |
96.2876 |
96.2781 |
| LR_15[cache_size=0.001,treshold=0.5] |
85.2248 |
85.0531 |
85.1286 |
85.1284 |
| LR_15[cache_size=0.001,treshold=0.6] |
71.6985 |
71.619 |
71.6749 |
71.6917 |
| LR_15[cache_size=0.001,treshold=0.7] |
43.0687 |
42.8563 |
43.0001 |
43.0077 |
| LR_15[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=All,treshold=0.3] |
98.6291 |
62.5759 |
86.6398 |
92.97 |
| LR_15[cache_size=All,treshold=0.5] |
76.5466 |
0.0168294 |
25.826 |
8.15949 |
| LR_15[cache_size=All,treshold=0.6] |
41.494 |
0.00192784 |
8.57445 |
0.267203 |
| LR_15[cache_size=All,treshold=0.7] |
1.02866 |
0 |
0.2232 |
5.25918e-05 |
| LR_15[cache_size=All,treshold=0.8] |
0.995167 |
0 |
0.215979 |
1.05184e-05 |
| LR_15[cache_size=All,treshold=0.9] |
0.984917 |
0 |
0.213844 |
0 |
| LR_1[cache_size=0.001,treshold=0.5] |
62.5772 |
62.4366 |
62.5263 |
62.548 |
| LR_1[cache_size=All,treshold=0.5] |
88.1376 |
24.3378 |
56.6328 |
57.3216 |
| LR_1_log[cache_size=0.001,treshold=0.5] |
93.7563 |
93.6125 |
93.6617 |
93.6419 |
| LR_1_log[cache_size=All,treshold=0.5] |
74.0881 |
1.75775 |
39.7855 |
43.6229 |
| LR_1_mean[cache_size=0.001,treshold=0.5] |
93.7312 |
93.6095 |
93.6675 |
93.6558 |
| LR_1_mean[cache_size=All,treshold=0.5] |
79.3058 |
0.00599916 |
26.8244 |
4.33355 |
| LR_1_robust_scaler[cache_size=0.001,treshold=0.5] |
62.5742 |
62.4346 |
62.5247 |
62.554 |
| LR_1_robust_scaler[cache_size=All,treshold=0.5] |
88.1376 |
24.3408 |
56.6349 |
57.3157 |
| LR_1_std_scaler[cache_size=0.001,treshold=0.5] |
62.5812 |
62.4436 |
62.5329 |
62.559 |
| LR_1_std_scaler[cache_size=All,treshold=0.5] |
88.1376 |
24.3374 |
56.6312 |
57.3216 |
| LR_2[cache_size=0.001,treshold=0.5] |
62.6652 |
62.5088 |
62.6214 |
62.6485 |
| LR_2[cache_size=All,treshold=0.5] |
88.1786 |
24.1566 |
56.5746 |
57.3379 |
| LR_2_log[cache_size=0.001,treshold=0.5] |
85.1767 |
85.0075 |
85.0798 |
85.0755 |
| LR_2_log[cache_size=All,treshold=0.5] |
74.2304 |
0 |
39.853 |
44.4229 |
| LR_2_mean[cache_size=0.001,treshold=0.5] |
85.1947 |
85.0301 |
85.0848 |
85.0805 |
| LR_2_mean[cache_size=All,treshold=0.5] |
79.8171 |
0 |
26.303 |
0.228452 |
| LR_3[cache_size=0.001,treshold=0.5] |
58.7067 |
58.5526 |
58.6331 |
58.6431 |
| LR_3[cache_size=All,treshold=0.5] |
88.1786 |
24.1497 |
56.5727 |
57.3377 |
| LR_3_log[cache_size=0.001,treshold=0.5] |
75.224 |
75.0761 |
75.1469 |
75.1551 |
| LR_3_log[cache_size=All,treshold=0.5] |
74.2133 |
0 |
39.7005 |
44.0943 |
| LR_3_mean[cache_size=0.001,treshold=0.5] |
75.2169 |
75.0741 |
75.1443 |
75.1541 |
| LR_3_mean[cache_size=All,treshold=0.5] |
79.7302 |
0 |
26.2389 |
0.209001 |
| LR_4[cache_size=0.001,treshold=0.5] |
62.5632 |
62.4336 |
62.5149 |
62.5361 |
| LR_4[cache_size=All,treshold=0.5] |
100 |
52.3813 |
79.8406 |
84.6044 |
| LR_4_log[cache_size=0.001,treshold=0.5] |
93.7563 |
93.6024 |
93.6605 |
93.6379 |
| LR_4_log[cache_size=All,treshold=0.5] |
96.2842 |
52.1274 |
72.1733 |
67.123 |
| LR_4_mean[cache_size=0.001,treshold=0.5] |
93.7342 |
93.6055 |
93.6677 |
93.6579 |
| LR_4_mean[cache_size=All,treshold=0.5] |
95.2114 |
51.1783 |
71.2989 |
66.6581 |
| LR_4_robust_scaler[cache_size=0.001,treshold=0.5] |
62.5686 |
62.4256 |
62.5193 |
62.543 |
| LR_4_robust_scaler[cache_size=All,treshold=0.5] |
100 |
53.0489 |
82.7424 |
93.7235 |
| LR_4_std_scaler[cache_size=0.001,treshold=0.5] |
62.5712 |
62.4316 |
62.5207 |
62.545 |
| LR_4_std_scaler[cache_size=All,treshold=0.5] |
100 |
53.0511 |
82.7339 |
93.6992 |
| LR_5[cache_size=0.001,treshold=0.5] |
58.7166 |
58.5666 |
58.6464 |
58.6561 |
| LR_5[cache_size=All,treshold=0.5] |
100 |
53.058 |
82.7467 |
93.7299 |
| LR_5_imba[cache_size=0.001,treshold=0.5] |
100 |
100 |
100 |
100 |
| LR_5_imba[cache_size=All,treshold=0.5] |
100 |
74.8512 |
94.9643 |
100 |
| LR_6[cache_size=0.001,treshold=0.5] |
58.7166 |
58.5666 |
58.6466 |
58.6571 |
| LR_6[cache_size=All,treshold=0.5] |
100 |
53.0567 |
82.7448 |
93.7252 |
| LR_6_imba[cache_size=0.001,treshold=0.5] |
100 |
100 |
100 |
100 |
| LR_6_imba[cache_size=All,treshold=0.5] |
100 |
74.8538 |
94.9643 |
100 |
| LR_7[cache_size=0.001,treshold=0.3] |
97.5571 |
97.4626 |
97.4992 |
97.4882 |
| LR_7[cache_size=0.001,treshold=0.5] |
93.7503 |
93.623 |
93.6585 |
93.6339 |
| LR_7[cache_size=0.001,treshold=0.6] |
87.1094 |
86.9658 |
87.0477 |
87.0595 |
| LR_7[cache_size=0.001,treshold=0.7] |
26.3669 |
25.9094 |
26.148 |
26.1589 |
| LR_7[cache_size=0.001,treshold=0.8] |
1.64238 |
1.59578 |
1.61903 |
1.6217 |
| LR_7[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=All,treshold=0.3] |
95.1715 |
72.7889 |
84.2368 |
85.8594 |
| LR_7[cache_size=All,treshold=0.5] |
73.1029 |
38.4053 |
56.871 |
61.8199 |
| LR_7[cache_size=All,treshold=0.6] |
58.3081 |
16.0942 |
36.825 |
31.9636 |
| LR_7[cache_size=All,treshold=0.7] |
53.2996 |
2.63038 |
24.5411 |
12.5872 |
| LR_7[cache_size=All,treshold=0.8] |
47.1457 |
0.168942 |
19.3419 |
6.2512 |
| LR_7[cache_size=All,treshold=0.9] |
37.938 |
0.00257741 |
14.5401 |
2.15885 |
| LR_8[cache_size=0.001,treshold=0.3] |
91.9068 |
91.6789 |
91.737 |
91.6959 |
| LR_8[cache_size=0.001,treshold=0.5] |
75.224 |
75.0761 |
75.1469 |
75.1551 |
| LR_8[cache_size=0.001,treshold=0.6] |
58.7067 |
58.5526 |
58.6331 |
58.6431 |
| LR_8[cache_size=0.001,treshold=0.7] |
33.7246 |
33.2856 |
33.5811 |
33.7083 |
| LR_8[cache_size=0.001,treshold=0.8] |
0.0280814 |
0.011942 |
0.0174121 |
0.0159978 |
| LR_8[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=All,treshold=0.3] |
95.1364 |
73.8602 |
84.4348 |
85.7619 |
| LR_8[cache_size=All,treshold=0.5] |
73.0882 |
38.2458 |
57.0313 |
61.8875 |
| LR_8[cache_size=All,treshold=0.6] |
59.4685 |
16.0466 |
37.0996 |
32.2961 |
| LR_8[cache_size=All,treshold=0.7] |
54.3847 |
2.6458 |
24.7665 |
12.5139 |
| LR_8[cache_size=All,treshold=0.8] |
48.4204 |
0.169078 |
19.594 |
6.2073 |
| LR_8[cache_size=All,treshold=0.9] |
38.7875 |
0.00256503 |
14.7166 |
2.13942 |
| LR_9[cache_size=0.001,treshold=0.3] |
96.3752 |
96.195 |
96.2502 |
96.2215 |
| LR_9[cache_size=0.001,treshold=0.5] |
85.1687 |
85.0145 |
85.0789 |
85.0477 |
| LR_9[cache_size=0.001,treshold=0.6] |
71.7115 |
71.6316 |
71.6629 |
71.6567 |
| LR_9[cache_size=0.001,treshold=0.7] |
43.1015 |
42.8623 |
43.0062 |
43.0327 |
| LR_9[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=All,treshold=0.3] |
95.1994 |
71.6255 |
84.0063 |
85.9408 |
| LR_9[cache_size=All,treshold=0.5] |
73.0953 |
38.5439 |
56.6746 |
61.7484 |
| LR_9[cache_size=All,treshold=0.6] |
57.255 |
16.1337 |
36.5584 |
31.5905 |
| LR_9[cache_size=All,treshold=0.7] |
52.2616 |
2.61461 |
24.3469 |
12.6649 |
| LR_9[cache_size=All,treshold=0.8] |
46.1398 |
0.169103 |
19.1538 |
6.30023 |
| LR_9[cache_size=All,treshold=0.9] |
37.0043 |
0.00262691 |
14.3603 |
2.18227 |
| LR_10[cache_size=0.01,treshold=0.3] |
97.375 |
97.3163 |
97.3478 |
97.3536 |
| LR_10[cache_size=0.01,treshold=0.5] |
94.6888 |
94.6161 |
94.656 |
94.6633 |
| LR_10[cache_size=0.01,treshold=0.6] |
90.3682 |
90.2595 |
90.3135 |
90.3117 |
| LR_10[cache_size=0.01,treshold=0.7] |
6.03174 |
5.94003 |
6.00207 |
6.01526 |
| LR_10[cache_size=0.01,treshold=0.8] |
0.00050356 |
0 |
0.000241275 |
0.000200983 |
| LR_10[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.01,treshold=0.3] |
94.3315 |
94.2582 |
94.287 |
94.2818 |
| LR_11[cache_size=0.01,treshold=0.5] |
80.6643 |
80.5771 |
80.6194 |
80.6123 |
| LR_11[cache_size=0.01,treshold=0.6] |
66.8483 |
66.7207 |
66.7776 |
66.7719 |
| LR_11[cache_size=0.01,treshold=0.7] |
40.5801 |
40.509 |
40.5422 |
40.5384 |
| LR_11[cache_size=0.01,treshold=0.8] |
1.44608 |
1.41296 |
1.43248 |
1.43323 |
| LR_11[cache_size=0.01,treshold=0.9] |
0.00421799 |
0.0023063 |
0.00359838 |
0.00382705 |
| LR_12[cache_size=0.01,treshold=0.3] |
95.5653 |
95.4966 |
95.5278 |
95.521 |
| LR_12[cache_size=0.01,treshold=0.5] |
84.6144 |
84.5207 |
84.5513 |
84.5412 |
| LR_12[cache_size=0.01,treshold=0.6] |
71.4212 |
71.3477 |
71.3724 |
71.3584 |
| LR_12[cache_size=0.01,treshold=0.7] |
42.1164 |
42.0782 |
42.0978 |
42.1007 |
| LR_12[cache_size=0.01,treshold=0.8] |
1.42588 |
1.39571 |
1.41357 |
1.41188 |
| LR_12[cache_size=0.01,treshold=0.9] |
0.00713041 |
0.00401096 |
0.00576894 |
0.00613557 |
| LR_13[cache_size=0.01,treshold=0.3] |
97.3731 |
97.3151 |
97.3462 |
97.3519 |
| LR_13[cache_size=0.01,treshold=0.5] |
94.6805 |
94.6052 |
94.6481 |
94.657 |
| LR_13[cache_size=0.01,treshold=0.6] |
90.3742 |
90.2749 |
90.324 |
90.3247 |
| LR_13[cache_size=0.01,treshold=0.7] |
8.03698 |
8.00667 |
8.02649 |
8.03409 |
| LR_13[cache_size=0.01,treshold=0.8] |
0.000100712 |
0 |
2.01424e-05 |
0 |
| LR_13[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.01,treshold=0.3] |
93.9165 |
93.8404 |
93.8637 |
93.851 |
| LR_14[cache_size=0.01,treshold=0.5] |
81.5645 |
81.4569 |
81.4959 |
81.4904 |
| LR_14[cache_size=0.01,treshold=0.6] |
68.2926 |
68.2366 |
68.2604 |
68.249 |
| LR_14[cache_size=0.01,treshold=0.7] |
41.2829 |
41.1636 |
41.1976 |
41.1719 |
| LR_14[cache_size=0.01,treshold=0.8] |
2.83379 |
2.79279 |
2.80859 |
2.80884 |
| LR_14[cache_size=0.01,treshold=0.9] |
0.00210899 |
0.000802192 |
0.00156809 |
0.00161139 |
| LR_15[cache_size=0.01,treshold=0.3] |
95.6961 |
95.6312 |
95.6606 |
95.655 |
| LR_15[cache_size=0.01,treshold=0.5] |
85.2907 |
85.2006 |
85.2238 |
85.2046 |
| LR_15[cache_size=0.01,treshold=0.6] |
72.1813 |
72.103 |
72.1346 |
72.1318 |
| LR_15[cache_size=0.01,treshold=0.7] |
41.1227 |
41.0181 |
41.0454 |
41.0263 |
| LR_15[cache_size=0.01,treshold=0.8] |
2.16584 |
2.13363 |
2.14395 |
2.14157 |
| LR_15[cache_size=0.01,treshold=0.9] |
0.00200857 |
0.000701918 |
0.00146762 |
0.00160933 |
| LR_1[cache_size=0.01,treshold=0.5] |
62.2952 |
62.1761 |
62.2345 |
62.2333 |
| LR_1_log[cache_size=0.01,treshold=0.5] |
94.6923 |
94.6112 |
94.655 |
94.6594 |
| LR_1_mean[cache_size=0.01,treshold=0.5] |
94.6919 |
94.6182 |
94.6592 |
94.6623 |
| LR_1_robust_scaler[cache_size=0.01,treshold=0.5] |
62.3087 |
62.1962 |
62.2506 |
62.2502 |
| LR_1_std_scaler[cache_size=0.01,treshold=0.5] |
62.3194 |
62.2084 |
62.2611 |
62.2611 |
| LR_2[cache_size=0.01,treshold=0.5] |
62.2958 |
62.1758 |
62.233 |
62.2276 |
| LR_2_log[cache_size=0.01,treshold=0.5] |
83.9115 |
83.8116 |
83.8511 |
83.8435 |
| LR_2_mean[cache_size=0.01,treshold=0.5] |
83.9008 |
83.8098 |
83.8459 |
83.841 |
| LR_3[cache_size=0.01,treshold=0.5] |
62.4219 |
62.3151 |
62.3656 |
62.3627 |
| LR_3_log[cache_size=0.01,treshold=0.5] |
79.617 |
79.5181 |
79.5735 |
79.5634 |
| LR_3_mean[cache_size=0.01,treshold=0.5] |
79.4844 |
79.3878 |
79.4419 |
79.4328 |
| LR_4[cache_size=0.01,treshold=0.5] |
62.2967 |
62.1778 |
62.2363 |
62.2343 |
| LR_4_log[cache_size=0.01,treshold=0.5] |
94.594 |
94.5106 |
94.5576 |
94.5648 |
| LR_4_mean[cache_size=0.01,treshold=0.5] |
94.5933 |
94.5108 |
94.557 |
94.5593 |
| LR_4_robust_scaler[cache_size=0.01,treshold=0.5] |
62.3154 |
62.203 |
62.2561 |
62.2557 |
| LR_4_std_scaler[cache_size=0.01,treshold=0.5] |
62.3149 |
62.2018 |
62.2562 |
62.2559 |
| LR_5[cache_size=0.01,treshold=0.5] |
62.3446 |
62.2334 |
62.2883 |
62.2846 |
| LR_5_imba[cache_size=0.01,treshold=0.5] |
100 |
100 |
100 |
100 |
| LR_6[cache_size=0.01,treshold=0.5] |
62.3734 |
62.2637 |
62.3196 |
62.3173 |
| LR_6_imba[cache_size=0.01,treshold=0.5] |
100 |
100 |
100 |
100 |
| LR_7[cache_size=0.01,treshold=0.3] |
97.3686 |
97.3096 |
97.3425 |
97.3482 |
| LR_7[cache_size=0.01,treshold=0.5] |
94.6936 |
94.6141 |
94.6562 |
94.6603 |
| LR_7[cache_size=0.01,treshold=0.6] |
90.3488 |
90.2492 |
90.2962 |
90.2923 |
| LR_7[cache_size=0.01,treshold=0.7] |
4.58652 |
4.53429 |
4.55233 |
4.54331 |
| LR_7[cache_size=0.01,treshold=0.8] |
0.000301475 |
0.000200548 |
0.000221094 |
0.000201166 |
| LR_7[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.01,treshold=0.3] |
94.2905 |
94.2105 |
94.2408 |
94.2346 |
| LR_8[cache_size=0.01,treshold=0.5] |
79.8408 |
79.7648 |
79.8063 |
79.7978 |
| LR_8[cache_size=0.01,treshold=0.6] |
66.1403 |
66.0341 |
66.092 |
66.086 |
| LR_8[cache_size=0.01,treshold=0.7] |
41.2065 |
41.1067 |
41.1406 |
41.1234 |
| LR_8[cache_size=0.01,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.01,treshold=0.3] |
95.4735 |
95.3989 |
95.4305 |
95.421 |
| LR_9[cache_size=0.01,treshold=0.5] |
83.9046 |
83.8062 |
83.8462 |
83.8416 |
| LR_9[cache_size=0.01,treshold=0.6] |
70.4536 |
70.3886 |
70.4178 |
70.413 |
| LR_9[cache_size=0.01,treshold=0.7] |
42.8521 |
42.7654 |
42.7949 |
42.774 |
| LR_9[cache_size=0.01,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.1,treshold=0.3] |
89.2643 |
89.2542 |
89.2601 |
89.263 |
| LR_10[cache_size=0.1,treshold=0.5] |
77.2598 |
77.2401 |
77.2519 |
77.2581 |
| LR_10[cache_size=0.1,treshold=0.6] |
62.1711 |
62.1222 |
62.1451 |
62.1468 |
| LR_10[cache_size=0.1,treshold=0.7] |
31.5959 |
31.5519 |
31.5796 |
31.5829 |
| LR_10[cache_size=0.1,treshold=0.8] |
2.13467 |
2.12937 |
2.13197 |
2.1317 |
| LR_10[cache_size=0.1,treshold=0.9] |
0.257826 |
0.253058 |
0.256527 |
0.257168 |
| LR_11[cache_size=0.1,treshold=0.3] |
89.1798 |
89.1671 |
89.1748 |
89.1782 |
| LR_11[cache_size=0.1,treshold=0.5] |
77.0769 |
77.0543 |
77.0672 |
77.0728 |
| LR_11[cache_size=0.1,treshold=0.6] |
62.1013 |
62.0506 |
62.0742 |
62.076 |
| LR_11[cache_size=0.1,treshold=0.7] |
31.6941 |
31.6538 |
31.6784 |
31.6804 |
| LR_11[cache_size=0.1,treshold=0.8] |
2.13293 |
2.12782 |
2.13011 |
2.12939 |
| LR_11[cache_size=0.1,treshold=0.9] |
0.262286 |
0.257266 |
0.260655 |
0.261218 |
| LR_12[cache_size=0.1,treshold=0.3] |
89.2823 |
89.2716 |
89.2776 |
89.2798 |
| LR_12[cache_size=0.1,treshold=0.5] |
77.3199 |
77.3019 |
77.3129 |
77.3191 |
| LR_12[cache_size=0.1,treshold=0.6] |
62.2521 |
62.2042 |
62.2253 |
62.2258 |
| LR_12[cache_size=0.1,treshold=0.7] |
31.5346 |
31.4921 |
31.519 |
31.5228 |
| LR_12[cache_size=0.1,treshold=0.8] |
2.09835 |
2.09459 |
2.09604 |
2.0948 |
| LR_12[cache_size=0.1,treshold=0.9] |
0.252683 |
0.24846 |
0.251711 |
0.252414 |
| LR_13[cache_size=0.1,treshold=0.3] |
85.7624 |
85.7447 |
85.7521 |
85.7507 |
| LR_13[cache_size=0.1,treshold=0.5] |
77.6022 |
77.5651 |
77.5868 |
77.5921 |
| LR_13[cache_size=0.1,treshold=0.6] |
68.6033 |
68.5457 |
68.5775 |
68.5855 |
| LR_13[cache_size=0.1,treshold=0.7] |
15.2344 |
15.1752 |
15.2046 |
15.2071 |
| LR_13[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.1,treshold=0.3] |
85.7079 |
85.6903 |
85.698 |
85.6963 |
| LR_14[cache_size=0.1,treshold=0.5] |
76.0659 |
76.0278 |
76.0474 |
76.0461 |
| LR_14[cache_size=0.1,treshold=0.6] |
66.5266 |
66.4793 |
66.499 |
66.4994 |
| LR_14[cache_size=0.1,treshold=0.7] |
23.3943 |
23.3549 |
23.3742 |
23.371 |
| LR_14[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.1,treshold=0.3] |
85.7083 |
85.6905 |
85.6983 |
85.6966 |
| LR_15[cache_size=0.1,treshold=0.5] |
76.0658 |
76.0278 |
76.0474 |
76.0461 |
| LR_15[cache_size=0.1,treshold=0.6] |
66.5255 |
66.4775 |
66.4974 |
66.4975 |
| LR_15[cache_size=0.1,treshold=0.7] |
23.5234 |
23.4831 |
23.5022 |
23.4977 |
| LR_15[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_1[cache_size=0.1,treshold=0.5] |
56.2671 |
56.2104 |
56.2381 |
56.2437 |
| LR_1_log[cache_size=0.1,treshold=0.5] |
74.5923 |
74.557 |
74.5742 |
74.5806 |
| LR_1_mean[cache_size=0.1,treshold=0.5] |
74.6141 |
74.5823 |
74.6006 |
74.6057 |
| LR_1_robust_scaler[cache_size=0.1,treshold=0.5] |
56.2653 |
56.2094 |
56.2363 |
56.2418 |
| LR_1_std_scaler[cache_size=0.1,treshold=0.5] |
56.2574 |
56.2013 |
56.2282 |
56.2341 |
| LR_2[cache_size=0.1,treshold=0.5] |
56.2667 |
56.2089 |
56.2362 |
56.2418 |
| LR_2_log[cache_size=0.1,treshold=0.5] |
71.4284 |
71.3881 |
71.4127 |
71.4194 |
| LR_2_mean[cache_size=0.1,treshold=0.5] |
71.4642 |
71.4261 |
71.4507 |
71.4586 |
| LR_3[cache_size=0.1,treshold=0.5] |
56.2694 |
56.2124 |
56.2398 |
56.2461 |
| LR_3_log[cache_size=0.1,treshold=0.5] |
71.2801 |
71.2414 |
71.2668 |
71.2756 |
| LR_3_mean[cache_size=0.1,treshold=0.5] |
71.302 |
71.2627 |
71.2874 |
71.2962 |
| LR_4[cache_size=0.1,treshold=0.5] |
56.698 |
56.6401 |
56.6708 |
56.6792 |
| LR_4_log[cache_size=0.1,treshold=0.5] |
75.412 |
75.3854 |
75.4 |
75.4046 |
| LR_4_mean[cache_size=0.1,treshold=0.5] |
75.3846 |
75.3563 |
75.3728 |
75.3771 |
| LR_4_robust_scaler[cache_size=0.1,treshold=0.5] |
56.7 |
56.6414 |
56.6718 |
56.677 |
| LR_4_std_scaler[cache_size=0.1,treshold=0.5] |
56.6974 |
56.639 |
56.6696 |
56.6757 |
| LR_5[cache_size=0.1,treshold=0.5] |
56.6922 |
56.6342 |
56.6641 |
56.6704 |
| LR_5_imba[cache_size=0.1,treshold=0.5] |
100 |
99.9999 |
100 |
100 |
| LR_6[cache_size=0.1,treshold=0.5] |
56.6997 |
56.6416 |
56.6716 |
56.6772 |
| LR_6_imba[cache_size=0.1,treshold=0.5] |
100 |
99.9999 |
100 |
100 |
| LR_7[cache_size=0.1,treshold=0.3] |
89.4207 |
89.4013 |
89.4085 |
89.404 |
| LR_7[cache_size=0.1,treshold=0.5] |
74.6101 |
74.5765 |
74.5935 |
74.5995 |
| LR_7[cache_size=0.1,treshold=0.6] |
59.0326 |
58.9805 |
59.0047 |
59.0117 |
| LR_7[cache_size=0.1,treshold=0.7] |
28.4263 |
28.3778 |
28.4064 |
28.4082 |
| LR_7[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.1,treshold=0.3] |
87.8624 |
87.8457 |
87.8534 |
87.8523 |
| LR_8[cache_size=0.1,treshold=0.5] |
71.306 |
71.2659 |
71.2896 |
71.2975 |
| LR_8[cache_size=0.1,treshold=0.6] |
56.6264 |
56.5704 |
56.5977 |
56.6045 |
| LR_8[cache_size=0.1,treshold=0.7] |
31.677 |
31.6262 |
31.6543 |
31.6554 |
| LR_8[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.1,treshold=0.3] |
87.9638 |
87.9473 |
87.9551 |
87.9535 |
| LR_9[cache_size=0.1,treshold=0.5] |
71.4639 |
71.4227 |
71.4479 |
71.4568 |
| LR_9[cache_size=0.1,treshold=0.6] |
56.7316 |
56.6757 |
56.7036 |
56.7094 |
| LR_9[cache_size=0.1,treshold=0.7] |
31.5653 |
31.513 |
31.5425 |
31.5428 |
| LR_9[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.2,treshold=0.3] |
83.5961 |
83.5694 |
83.5792 |
83.5753 |
| LR_10[cache_size=0.2,treshold=0.5] |
68.5525 |
68.5371 |
68.545 |
68.5465 |
| LR_10[cache_size=0.2,treshold=0.6] |
55.0807 |
55.0695 |
55.073 |
55.0709 |
| LR_10[cache_size=0.2,treshold=0.7] |
20.0306 |
20.0094 |
20.0186 |
20.0145 |
| LR_10[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.2,treshold=0.3] |
83.6025 |
83.5758 |
83.5855 |
83.5816 |
| LR_11[cache_size=0.2,treshold=0.5] |
68.9088 |
68.8911 |
68.8993 |
68.901 |
| LR_11[cache_size=0.2,treshold=0.6] |
55.2445 |
55.2327 |
55.2358 |
55.2336 |
| LR_11[cache_size=0.2,treshold=0.7] |
19.5682 |
19.5445 |
19.5556 |
19.5541 |
| LR_11[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.2,treshold=0.3] |
83.5937 |
83.5671 |
83.5768 |
83.5727 |
| LR_12[cache_size=0.2,treshold=0.5] |
69.2713 |
69.2555 |
69.2636 |
69.2649 |
| LR_12[cache_size=0.2,treshold=0.6] |
55.3333 |
55.3201 |
55.3243 |
55.3227 |
| LR_12[cache_size=0.2,treshold=0.7] |
19.1504 |
19.1237 |
19.1382 |
19.1369 |
| LR_12[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.2,treshold=0.3] |
85.1814 |
85.1577 |
85.167 |
85.1645 |
| LR_13[cache_size=0.2,treshold=0.5] |
67.1231 |
67.1173 |
67.1204 |
67.1213 |
| LR_13[cache_size=0.2,treshold=0.6] |
49.1877 |
49.1653 |
49.1735 |
49.1699 |
| LR_13[cache_size=0.2,treshold=0.7] |
17.1856 |
17.1694 |
17.1774 |
17.1748 |
| LR_13[cache_size=0.2,treshold=0.8] |
0.00191122 |
0.00171103 |
0.00182223 |
0.00184962 |
| LR_13[cache_size=0.2,treshold=0.9] |
0.000725711 |
0.000609103 |
0.000666862 |
0.000670311 |
| LR_14[cache_size=0.2,treshold=0.3] |
85.1966 |
85.174 |
85.1825 |
85.1797 |
| LR_14[cache_size=0.2,treshold=0.5] |
67.0779 |
67.0718 |
67.0754 |
67.0765 |
| LR_14[cache_size=0.2,treshold=0.6] |
49.0908 |
49.0709 |
49.0774 |
49.073 |
| LR_14[cache_size=0.2,treshold=0.7] |
17.0192 |
17.0031 |
17.0112 |
17.0085 |
| LR_14[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.2,treshold=0.3] |
85.2582 |
85.2335 |
85.2436 |
85.2404 |
| LR_15[cache_size=0.2,treshold=0.5] |
67.1184 |
67.1115 |
67.1154 |
67.1163 |
| LR_15[cache_size=0.2,treshold=0.6] |
49.114 |
49.0932 |
49.1003 |
49.0966 |
| LR_15[cache_size=0.2,treshold=0.7] |
16.8604 |
16.847 |
16.8534 |
16.8522 |
| LR_15[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_1[cache_size=0.2,treshold=0.5] |
50.8807 |
50.852 |
50.8624 |
50.8601 |
| LR_1_log[cache_size=0.2,treshold=0.5] |
64.4573 |
64.4455 |
64.451 |
64.4512 |
| LR_1_mean[cache_size=0.2,treshold=0.5] |
64.5222 |
64.5142 |
64.5182 |
64.5174 |
| LR_1_robust_scaler[cache_size=0.2,treshold=0.5] |
50.8836 |
50.8524 |
50.8645 |
50.8624 |
| LR_1_std_scaler[cache_size=0.2,treshold=0.5] |
50.8785 |
50.8483 |
50.8599 |
50.8581 |
| LR_2[cache_size=0.2,treshold=0.5] |
50.8793 |
50.8507 |
50.8605 |
50.8573 |
| LR_2_log[cache_size=0.2,treshold=0.5] |
64.5742 |
64.5645 |
64.5684 |
64.5687 |
| LR_2_mean[cache_size=0.2,treshold=0.5] |
64.6566 |
64.6486 |
64.6515 |
64.6496 |
| LR_3[cache_size=0.2,treshold=0.5] |
50.875 |
50.8473 |
50.8564 |
50.8531 |
| LR_3_log[cache_size=0.2,treshold=0.5] |
64.5293 |
64.5195 |
64.5233 |
64.5228 |
| LR_3_mean[cache_size=0.2,treshold=0.5] |
64.6031 |
64.5946 |
64.5977 |
64.5957 |
| LR_4[cache_size=0.2,treshold=0.5] |
52.3069 |
52.2818 |
52.2895 |
52.2868 |
| LR_4_log[cache_size=0.2,treshold=0.5] |
65.5247 |
65.5156 |
65.5194 |
65.518 |
| LR_4_mean[cache_size=0.2,treshold=0.5] |
65.4767 |
65.4675 |
65.4722 |
65.4713 |
| LR_4_robust_scaler[cache_size=0.2,treshold=0.5] |
52.3161 |
52.2918 |
52.299 |
52.2956 |
| LR_4_std_scaler[cache_size=0.2,treshold=0.5] |
52.3144 |
52.2895 |
52.297 |
52.2932 |
| LR_5[cache_size=0.2,treshold=0.5] |
52.307 |
52.2816 |
52.2894 |
52.2864 |
| LR_5_imba[cache_size=0.2,treshold=0.5] |
86.7098 |
86.6824 |
86.6945 |
86.6935 |
| LR_6[cache_size=0.2,treshold=0.5] |
52.3016 |
52.2765 |
52.2839 |
52.2808 |
| LR_6_imba[cache_size=0.2,treshold=0.5] |
86.7002 |
86.6735 |
86.6851 |
86.6837 |
| LR_7[cache_size=0.2,treshold=0.3] |
83.7699 |
83.747 |
83.755 |
83.7504 |
| LR_7[cache_size=0.2,treshold=0.5] |
64.4387 |
64.4283 |
64.4317 |
64.43 |
| LR_7[cache_size=0.2,treshold=0.6] |
47.9629 |
47.9344 |
47.9486 |
47.9476 |
| LR_7[cache_size=0.2,treshold=0.7] |
20.5382 |
20.516 |
20.5278 |
20.525 |
| LR_7[cache_size=0.2,treshold=0.8] |
0.000714631 |
0.000564855 |
0.000634739 |
0.000631533 |
| LR_7[cache_size=0.2,treshold=0.9] |
4.9858e-05 |
2.21512e-05 |
3.54487e-05 |
3.3232e-05 |
| LR_8[cache_size=0.2,treshold=0.3] |
83.9088 |
83.8831 |
83.8913 |
83.8872 |
| LR_8[cache_size=0.2,treshold=0.5] |
64.5758 |
64.5667 |
64.5704 |
64.5701 |
| LR_8[cache_size=0.2,treshold=0.6] |
47.9949 |
47.9657 |
47.9799 |
47.9789 |
| LR_8[cache_size=0.2,treshold=0.7] |
20.2506 |
20.2309 |
20.2397 |
20.2356 |
| LR_8[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.2,treshold=0.3] |
83.9717 |
83.9454 |
83.9533 |
83.9483 |
| LR_9[cache_size=0.2,treshold=0.5] |
64.6332 |
64.6245 |
64.6284 |
64.629 |
| LR_9[cache_size=0.2,treshold=0.6] |
47.9965 |
47.9664 |
47.9809 |
47.9793 |
| LR_9[cache_size=0.2,treshold=0.7] |
20.0841 |
20.066 |
20.0744 |
20.0708 |
| LR_9[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.4,treshold=0.3] |
76.9303 |
76.908 |
76.9145 |
76.9106 |
| LR_10[cache_size=0.4,treshold=0.5] |
50.9489 |
50.9349 |
50.9438 |
50.9464 |
| LR_10[cache_size=0.4,treshold=0.6] |
34.15 |
34.1391 |
34.1443 |
34.1449 |
| LR_10[cache_size=0.4,treshold=0.7] |
9.13262 |
9.11202 |
9.12143 |
9.11759 |
| LR_10[cache_size=0.4,treshold=0.8] |
0.0186612 |
0.017784 |
0.0181582 |
0.0181346 |
| LR_10[cache_size=0.4,treshold=0.9] |
0.0109344 |
0.0102446 |
0.0105435 |
0.0104426 |
| LR_11[cache_size=0.4,treshold=0.3] |
77.1578 |
77.0879 |
77.1189 |
77.1225 |
| LR_11[cache_size=0.4,treshold=0.5] |
50.9136 |
50.8969 |
50.9072 |
50.9101 |
| LR_11[cache_size=0.4,treshold=0.6] |
33.9787 |
33.9651 |
33.9714 |
33.9717 |
| LR_11[cache_size=0.4,treshold=0.7] |
8.73736 |
8.64091 |
8.68815 |
8.69015 |
| LR_11[cache_size=0.4,treshold=0.8] |
0.00832935 |
0.00766682 |
0.00807639 |
0.00805432 |
| LR_11[cache_size=0.4,treshold=0.9] |
0.00205078 |
0.00181006 |
0.00189812 |
0.00188746 |
| LR_12[cache_size=0.4,treshold=0.3] |
77.2316 |
77.2054 |
77.2139 |
77.2129 |
| LR_12[cache_size=0.4,treshold=0.5] |
50.9266 |
50.9126 |
50.9215 |
50.9242 |
| LR_12[cache_size=0.4,treshold=0.6] |
33.9334 |
33.9216 |
33.9271 |
33.9277 |
| LR_12[cache_size=0.4,treshold=0.7] |
8.54139 |
8.51295 |
8.52589 |
8.52181 |
| LR_12[cache_size=0.4,treshold=0.8] |
0.00810039 |
0.00762969 |
0.00791551 |
0.00798041 |
| LR_12[cache_size=0.4,treshold=0.9] |
0.00197345 |
0.00178531 |
0.00186192 |
0.00184709 |
| LR_13[cache_size=0.4,treshold=0.3] |
79.7959 |
79.7707 |
79.7821 |
79.7794 |
| LR_13[cache_size=0.4,treshold=0.5] |
56.8821 |
56.8772 |
56.8796 |
56.8796 |
| LR_13[cache_size=0.4,treshold=0.6] |
37.4317 |
37.4198 |
37.4265 |
37.4261 |
| LR_13[cache_size=0.4,treshold=0.7] |
4.59219 |
4.56944 |
4.58143 |
4.58078 |
| LR_13[cache_size=0.4,treshold=0.8] |
0.00822766 |
0.00764558 |
0.00791799 |
0.00784122 |
| LR_13[cache_size=0.4,treshold=0.9] |
0.00372859 |
0.00342191 |
0.00353946 |
0.00352004 |
| LR_14[cache_size=0.4,treshold=0.3] |
79.7923 |
79.7675 |
79.7787 |
79.7763 |
| LR_14[cache_size=0.4,treshold=0.5] |
56.8712 |
56.8663 |
56.8686 |
56.8685 |
| LR_14[cache_size=0.4,treshold=0.6] |
37.4622 |
37.4499 |
37.4573 |
37.4572 |
| LR_14[cache_size=0.4,treshold=0.7] |
4.6881 |
4.66267 |
4.67491 |
4.67321 |
| LR_14[cache_size=0.4,treshold=0.8] |
0.00791513 |
0.00743518 |
0.00766738 |
0.00765872 |
| LR_14[cache_size=0.4,treshold=0.9] |
0.00371931 |
0.00340026 |
0.00353265 |
0.00352004 |
| LR_15[cache_size=0.4,treshold=0.3] |
79.8184 |
79.7927 |
79.8045 |
79.8023 |
| LR_15[cache_size=0.4,treshold=0.5] |
56.8987 |
56.8941 |
56.8963 |
56.8963 |
| LR_15[cache_size=0.4,treshold=0.6] |
37.4239 |
37.4122 |
37.4186 |
37.4181 |
| LR_15[cache_size=0.4,treshold=0.7] |
4.51422 |
4.49214 |
4.50309 |
4.50226 |
| LR_15[cache_size=0.4,treshold=0.8] |
0.00824003 |
0.00772293 |
0.00794398 |
0.00786287 |
| LR_15[cache_size=0.4,treshold=0.9] |
0.00371621 |
0.00339407 |
0.00352523 |
0.00350458 |
| LR_1[cache_size=0.4,treshold=0.5] |
44.3925 |
44.3687 |
44.3807 |
44.382 |
| LR_1_log[cache_size=0.4,treshold=0.5] |
58.8533 |
58.8393 |
58.8452 |
58.8442 |
| LR_1_mean[cache_size=0.4,treshold=0.5] |
58.9896 |
58.9777 |
58.9825 |
58.9807 |
| LR_1_robust_scaler[cache_size=0.4,treshold=0.5] |
44.3926 |
44.3684 |
44.3808 |
44.3821 |
| LR_1_std_scaler[cache_size=0.4,treshold=0.5] |
44.3921 |
44.3676 |
44.3801 |
44.3816 |
| LR_2[cache_size=0.4,treshold=0.5] |
44.3922 |
44.3656 |
44.3794 |
44.3798 |
| LR_2_log[cache_size=0.4,treshold=0.5] |
58.9235 |
58.9101 |
58.916 |
58.9152 |
| LR_2_mean[cache_size=0.4,treshold=0.5] |
59.0887 |
59.0744 |
59.0821 |
59.0832 |
| LR_3[cache_size=0.4,treshold=0.5] |
44.3866 |
44.3595 |
44.3734 |
44.3741 |
| LR_3_log[cache_size=0.4,treshold=0.5] |
58.8898 |
58.876 |
58.8817 |
58.88 |
| LR_3_mean[cache_size=0.4,treshold=0.5] |
59.0535 |
59.0404 |
59.0479 |
59.0488 |
| LR_4[cache_size=0.4,treshold=0.5] |
47.3341 |
47.3161 |
47.3269 |
47.328 |
| LR_4_log[cache_size=0.4,treshold=0.5] |
57.66 |
57.6504 |
57.6545 |
57.6545 |
| LR_4_mean[cache_size=0.4,treshold=0.5] |
58.2127 |
58.1994 |
58.2039 |
58.2022 |
| LR_4_robust_scaler[cache_size=0.4,treshold=0.5] |
47.3341 |
47.3167 |
47.3268 |
47.3277 |
| LR_4_std_scaler[cache_size=0.4,treshold=0.5] |
47.3135 |
47.2966 |
47.3068 |
47.3078 |
| LR_5[cache_size=0.4,treshold=0.5] |
47.333 |
47.3153 |
47.3255 |
47.3264 |
| LR_5_imba[cache_size=0.4,treshold=0.5] |
63.8715 |
63.8557 |
63.8637 |
63.8643 |
| LR_6[cache_size=0.4,treshold=0.5] |
47.3246 |
47.3073 |
47.3174 |
47.3185 |
| LR_6_imba[cache_size=0.4,treshold=0.5] |
63.8617 |
63.8462 |
63.8543 |
63.8549 |
| LR_7[cache_size=0.4,treshold=0.3] |
82.6636 |
82.6517 |
82.6574 |
82.6576 |
| LR_7[cache_size=0.4,treshold=0.5] |
58.8613 |
58.8492 |
58.856 |
58.8576 |
| LR_7[cache_size=0.4,treshold=0.6] |
36.525 |
36.509 |
36.5186 |
36.5205 |
| LR_7[cache_size=0.4,treshold=0.7] |
0.0598249 |
0.0588934 |
0.0593094 |
0.0591997 |
| LR_7[cache_size=0.4,treshold=0.8] |
0.016233 |
0.0157954 |
0.0159684 |
0.015879 |
| LR_7[cache_size=0.4,treshold=0.9] |
0.0138327 |
0.0131252 |
0.0134153 |
0.0133349 |
| LR_8[cache_size=0.4,treshold=0.3] |
82.9483 |
82.9326 |
82.9406 |
82.9413 |
| LR_8[cache_size=0.4,treshold=0.5] |
59.0477 |
59.034 |
59.0413 |
59.0426 |
| LR_8[cache_size=0.4,treshold=0.6] |
36.3088 |
36.2915 |
36.3009 |
36.3037 |
| LR_8[cache_size=0.4,treshold=0.7] |
0.0377267 |
0.0364858 |
0.0368858 |
0.0365835 |
| LR_8[cache_size=0.4,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.4,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.4,treshold=0.3] |
83.0086 |
82.9942 |
83.0019 |
83.003 |
| LR_9[cache_size=0.4,treshold=0.5] |
59.0808 |
59.0669 |
59.0739 |
59.0748 |
| LR_9[cache_size=0.4,treshold=0.6] |
36.2503 |
36.2326 |
36.2417 |
36.243 |
| LR_9[cache_size=0.4,treshold=0.7] |
0.0369191 |
0.0353162 |
0.0359428 |
0.0356269 |
| LR_9[cache_size=0.4,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.4,treshold=0.9] |
0 |
0 |
0 |
0 |
| Offline Clock 1st iteration |
0 |
0 |
0 |
0 |
| Offline Clock 2nd iteration |
99.8119 |
59.132 |
82.3408 |
83.126 |
| Zipf Optimal Distribution |
99.9168 |
54.4937 |
83.9515 |
89.1265 |
Miss Ratio Reduced (%)
| Model |
Max |
Min |
Avg |
Mdn |
| LR_10[cache_size=0.001,treshold=0.3] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.001,treshold=0.6] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.001,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=All,treshold=0.3] |
0.00798719 |
-0.00362421 |
0.00086107 |
0.000202019 |
| LR_10[cache_size=All,treshold=0.5] |
0.00565776 |
-0.0019968 |
0.000724704 |
0.000101011 |
| LR_10[cache_size=All,treshold=0.6] |
0.00815363 |
-0.00183045 |
0.000486782 |
0 |
| LR_10[cache_size=All,treshold=0.7] |
0.00249601 |
-0.00282888 |
-1.46201e-05 |
0 |
| LR_10[cache_size=All,treshold=0.8] |
0.000333323 |
-0.000332784 |
1.1821e-05 |
0 |
| LR_10[cache_size=All,treshold=0.9] |
0.000444431 |
-0.000222218 |
-1.34833e-05 |
0 |
| LR_11[cache_size=0.001,treshold=0.3] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.001,treshold=0.6] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.001,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=All,treshold=0.3] |
0.00798719 |
-0.00374918 |
0.000828169 |
0.000202019 |
| LR_11[cache_size=All,treshold=0.5] |
0.00582416 |
-0.001664 |
0.000733458 |
0 |
| LR_11[cache_size=All,treshold=0.6] |
0.00881924 |
-0.00249607 |
0.000439082 |
0 |
| LR_11[cache_size=All,treshold=0.7] |
0.00299521 |
-0.00183045 |
0.000116297 |
0 |
| LR_11[cache_size=All,treshold=0.8] |
0.000499202 |
-0.0003328 |
6.41822e-06 |
0 |
| LR_11[cache_size=All,treshold=0.9] |
0.000444431 |
-0.000333327 |
-1.34835e-05 |
0 |
| LR_12[cache_size=0.001,treshold=0.3] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.001,treshold=0.6] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.001,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=All,treshold=0.3] |
0.00798719 |
-0.00362421 |
0.000874789 |
0.000202019 |
| LR_12[cache_size=All,treshold=0.5] |
0.00582416 |
-0.0014976 |
0.00073348 |
0 |
| LR_12[cache_size=All,treshold=0.6] |
0.00881924 |
-0.00332809 |
0.000474746 |
0 |
| LR_12[cache_size=All,treshold=0.7] |
0.0014976 |
-0.00133124 |
3.36536e-05 |
0 |
| LR_12[cache_size=All,treshold=0.8] |
0.000499202 |
-0.0003328 |
1.50536e-05 |
0 |
| LR_12[cache_size=All,treshold=0.9] |
0.000333323 |
-0.000222218 |
-9.03926e-06 |
0 |
| LR_13[cache_size=0.001,treshold=0.3] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.001,treshold=0.6] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.001,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=All,treshold=0.3] |
0.00815359 |
-0.00349923 |
0.000893184 |
0.000202019 |
| LR_13[cache_size=All,treshold=0.5] |
0.00798742 |
-0.0027494 |
0.000570512 |
0 |
| LR_13[cache_size=All,treshold=0.6] |
0.00698883 |
-0.00232966 |
0.000463697 |
0 |
| LR_13[cache_size=All,treshold=0.7] |
0 |
-0.000101011 |
-4.04044e-06 |
0 |
| LR_13[cache_size=All,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=All,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.001,treshold=0.3] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.001,treshold=0.6] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.001,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=All,treshold=0.3] |
0.00765439 |
-0.00362421 |
0.000956058 |
0.000303024 |
| LR_14[cache_size=All,treshold=0.5] |
0.00798742 |
-0.0027494 |
0.000578826 |
0 |
| LR_14[cache_size=All,treshold=0.6] |
0.00815363 |
-0.00216326 |
0.000490321 |
0 |
| LR_14[cache_size=All,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=All,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=All,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.001,treshold=0.3] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.001,treshold=0.6] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.001,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=All,treshold=0.3] |
0.00732159 |
-0.00362421 |
0.000975453 |
0.000303024 |
| LR_15[cache_size=All,treshold=0.5] |
0.00798742 |
-0.0027494 |
0.000577169 |
0 |
| LR_15[cache_size=All,treshold=0.6] |
0.00798723 |
-0.00266247 |
0.00045704 |
0 |
| LR_15[cache_size=All,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=All,treshold=0.8] |
0 |
-0.000101011 |
-4.04044e-06 |
0 |
| LR_15[cache_size=All,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_1[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_1[cache_size=All,treshold=0.5] |
0.00532482 |
-0.00188883 |
0.000525088 |
0.000101009 |
| LR_1_log[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_1_log[cache_size=All,treshold=0.5] |
0.0073218 |
-0.00277769 |
0.000580182 |
0.000101009 |
| LR_1_mean[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_1_mean[cache_size=All,treshold=0.5] |
0.00931796 |
-0.00224951 |
0.00058113 |
0 |
| LR_1_robust_scaler[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_1_robust_scaler[cache_size=All,treshold=0.5] |
0.00515842 |
-0.00199994 |
0.000537268 |
0 |
| LR_1_std_scaler[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_1_std_scaler[cache_size=All,treshold=0.5] |
0.00499202 |
-0.00199994 |
0.000510644 |
0 |
| LR_2[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_2[cache_size=All,treshold=0.5] |
0.00549122 |
-0.0031616 |
0.000404233 |
0.000101009 |
| LR_2_log[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_2_log[cache_size=All,treshold=0.5] |
0.0071554 |
-0.0029952 |
0.00060741 |
0.000101009 |
| LR_2_mean[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_2_mean[cache_size=All,treshold=0.5] |
0.00782043 |
-0.00274943 |
0.000632778 |
0 |
| LR_3[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_3[cache_size=All,treshold=0.5] |
0.00549122 |
-0.0031616 |
0.000398132 |
0.000101009 |
| LR_3_log[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_3_log[cache_size=All,treshold=0.5] |
0.0073218 |
-0.0031616 |
0.000559132 |
0.000101009 |
| LR_3_mean[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_3_mean[cache_size=All,treshold=0.5] |
0.00715486 |
-0.00287441 |
0.00056953 |
0 |
| LR_4[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_4[cache_size=All,treshold=0.5] |
0.00599043 |
-0.00374923 |
0.000425564 |
0.000202019 |
| LR_4_log[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_4_log[cache_size=All,treshold=0.5] |
0.00615683 |
-0.00224954 |
0.000678864 |
0.000202019 |
| LR_4_mean[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_4_mean[cache_size=All,treshold=0.5] |
0.00682243 |
-0.00324933 |
0.000653643 |
0.000202019 |
| LR_4_robust_scaler[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_4_robust_scaler[cache_size=All,treshold=0.5] |
0.00549199 |
-0.00374923 |
0.000408286 |
0.000101012 |
| LR_4_std_scaler[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_4_std_scaler[cache_size=All,treshold=0.5] |
0.00532557 |
-0.00374923 |
0.000411626 |
0.000101012 |
| LR_5[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_5[cache_size=All,treshold=0.5] |
0.00549199 |
-0.00374923 |
0.000405525 |
0.000101012 |
| LR_5_imba[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_5_imba[cache_size=All,treshold=0.5] |
0.0106499 |
-0.0027494 |
0.00114351 |
0.000111109 |
| LR_6[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_6[cache_size=All,treshold=0.5] |
0.00549199 |
-0.00374923 |
0.000410524 |
0.000101012 |
| LR_6_imba[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_6_imba[cache_size=All,treshold=0.5] |
0.0106499 |
-0.0027494 |
0.00114517 |
0.000111109 |
| LR_7[cache_size=0.001,treshold=0.3] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=0.001,treshold=0.6] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=0.001,treshold=0.7] |
0 |
-0.0001001 |
-2.002e-05 |
0 |
| LR_7[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=All,treshold=0.3] |
0.00499176 |
-0.0038742 |
0.000645072 |
0.000303024 |
| LR_7[cache_size=All,treshold=0.5] |
0.00981787 |
-0.00399918 |
0.000555027 |
0.000101009 |
| LR_7[cache_size=All,treshold=0.6] |
0.00532482 |
-0.00188883 |
0.000320982 |
0 |
| LR_7[cache_size=All,treshold=0.7] |
0.00149761 |
-0.00155551 |
-9.70986e-05 |
0 |
| LR_7[cache_size=All,treshold=0.8] |
0.000555525 |
-0.000888862 |
-1.58246e-05 |
0 |
| LR_7[cache_size=All,treshold=0.9] |
0.000124961 |
-0.000249935 |
-3.27375e-05 |
0 |
| LR_8[cache_size=0.001,treshold=0.3] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.001,treshold=0.6] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.001,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=All,treshold=0.3] |
0.00549094 |
-0.0038742 |
0.000693896 |
0.000303024 |
| LR_8[cache_size=All,treshold=0.5] |
0.00998427 |
-0.00399918 |
0.000548179 |
0.000101009 |
| LR_8[cache_size=All,treshold=0.6] |
0.00582402 |
-0.00188883 |
0.000281043 |
0 |
| LR_8[cache_size=All,treshold=0.7] |
0.00149761 |
-0.00166662 |
-8.65525e-05 |
0 |
| LR_8[cache_size=All,treshold=0.8] |
0.00066663 |
-0.000888862 |
-1.6379e-05 |
0 |
| LR_8[cache_size=All,treshold=0.9] |
0.000124961 |
-0.000249935 |
-3.27373e-05 |
0 |
| LR_9[cache_size=0.001,treshold=0.3] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.001,treshold=0.5] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.001,treshold=0.6] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.001,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.001,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.001,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=All,treshold=0.3] |
0.00499176 |
-0.00362425 |
0.000674895 |
0.000303024 |
| LR_9[cache_size=All,treshold=0.5] |
0.00965147 |
-0.00399918 |
0.0005532 |
0.000101009 |
| LR_9[cache_size=All,treshold=0.6] |
0.00482562 |
-0.00188883 |
0.000285484 |
0 |
| LR_9[cache_size=All,treshold=0.7] |
0.00133121 |
-0.00166662 |
-9.98647e-05 |
0 |
| LR_9[cache_size=All,treshold=0.8] |
0.00066663 |
-0.000888862 |
-9.16771e-06 |
0 |
| LR_9[cache_size=All,treshold=0.9] |
0.000124961 |
-0.000249935 |
-3.27375e-05 |
0 |
| LR_10[cache_size=0.01,treshold=0.3] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_10[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_10[cache_size=0.01,treshold=0.6] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_10[cache_size=0.01,treshold=0.7] |
0 |
-0.000101011 |
-4.04041e-05 |
0 |
| LR_10[cache_size=0.01,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.01,treshold=0.3] |
0.000404032 |
-0.000202021 |
0.000121211 |
0.000101012 |
| LR_11[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
8.08066e-05 |
0.000101011 |
| LR_11[cache_size=0.01,treshold=0.6] |
0.000202016 |
-0.000202021 |
4.04031e-05 |
0.000101009 |
| LR_11[cache_size=0.01,treshold=0.7] |
0.000202019 |
0 |
6.06053e-05 |
0 |
| LR_11[cache_size=0.01,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.01,treshold=0.3] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_12[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
8.08066e-05 |
0.000101011 |
| LR_12[cache_size=0.01,treshold=0.6] |
0.000202016 |
-0.000202021 |
4.04031e-05 |
0.000101009 |
| LR_12[cache_size=0.01,treshold=0.7] |
0.000202019 |
0 |
6.06053e-05 |
0 |
| LR_12[cache_size=0.01,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.01,treshold=0.3] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_13[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_13[cache_size=0.01,treshold=0.6] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_13[cache_size=0.01,treshold=0.7] |
0 |
-0.000101011 |
-4.04041e-05 |
0 |
| LR_13[cache_size=0.01,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.01,treshold=0.3] |
0.000404032 |
-0.000202021 |
0.000121211 |
0.000101012 |
| LR_14[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
8.08066e-05 |
0.000101011 |
| LR_14[cache_size=0.01,treshold=0.6] |
0.000202016 |
-0.000202021 |
4.04031e-05 |
0.000101009 |
| LR_14[cache_size=0.01,treshold=0.7] |
0.000202019 |
0 |
0.00010101 |
0.000101011 |
| LR_14[cache_size=0.01,treshold=0.8] |
0 |
-0.000101012 |
-2.02025e-05 |
0 |
| LR_14[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.01,treshold=0.3] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_15[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
8.08066e-05 |
0.000101011 |
| LR_15[cache_size=0.01,treshold=0.6] |
0.000202016 |
-0.000202021 |
4.04031e-05 |
0.000101009 |
| LR_15[cache_size=0.01,treshold=0.7] |
0.000202019 |
0 |
0.00010101 |
0.000101011 |
| LR_15[cache_size=0.01,treshold=0.8] |
0 |
-0.000101011 |
-4.04041e-05 |
0 |
| LR_15[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_1[cache_size=0.01,treshold=0.5] |
0.000202022 |
-0.00010101 |
6.06058e-05 |
0.000101008 |
| LR_1_log[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_1_mean[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_1_robust_scaler[cache_size=0.01,treshold=0.5] |
0.000202022 |
-0.00010101 |
6.06058e-05 |
0.000101008 |
| LR_1_std_scaler[cache_size=0.01,treshold=0.5] |
0.000202022 |
-0.00010101 |
6.06058e-05 |
0.000101008 |
| LR_2[cache_size=0.01,treshold=0.5] |
0.000202022 |
-0.00010101 |
6.06058e-05 |
0.000101008 |
| LR_2_log[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_2_mean[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_3[cache_size=0.01,treshold=0.5] |
0.000202022 |
-0.00010101 |
8.08083e-05 |
0.000101009 |
| LR_3_log[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_3_mean[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_4[cache_size=0.01,treshold=0.5] |
0.000202022 |
-0.00010101 |
6.06058e-05 |
0.000101008 |
| LR_4_log[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_4_mean[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_4_robust_scaler[cache_size=0.01,treshold=0.5] |
0.000202022 |
-0.00010101 |
6.06058e-05 |
0.000101008 |
| LR_4_std_scaler[cache_size=0.01,treshold=0.5] |
0.000202022 |
-0.00010101 |
6.06058e-05 |
0.000101008 |
| LR_5[cache_size=0.01,treshold=0.5] |
0.000202022 |
-0.00010101 |
6.06058e-05 |
0.000101008 |
| LR_5_imba[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_6[cache_size=0.01,treshold=0.5] |
0.000202022 |
-0.00010101 |
8.08083e-05 |
0.000101009 |
| LR_6_imba[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_7[cache_size=0.01,treshold=0.3] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_7[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_7[cache_size=0.01,treshold=0.6] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_7[cache_size=0.01,treshold=0.7] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=0.01,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.01,treshold=0.3] |
0.000404032 |
-0.000202021 |
0.000121211 |
0.000101012 |
| LR_8[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_8[cache_size=0.01,treshold=0.6] |
0.000202016 |
-0.000202021 |
4.04031e-05 |
0.000101009 |
| LR_8[cache_size=0.01,treshold=0.7] |
0.000202019 |
0 |
0.000101009 |
0.000101011 |
| LR_8[cache_size=0.01,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.01,treshold=0.3] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_9[cache_size=0.01,treshold=0.5] |
0.000303024 |
-0.000202021 |
0.000101009 |
0.000101012 |
| LR_9[cache_size=0.01,treshold=0.6] |
0.000202016 |
-0.00010101 |
8.08077e-05 |
0.000101011 |
| LR_9[cache_size=0.01,treshold=0.7] |
0.000202019 |
0 |
0.000101009 |
0.000101011 |
| LR_9[cache_size=0.01,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.01,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.1,treshold=0.3] |
0.000777762 |
-0.00211105 |
0.000133324 |
0.000666628 |
| LR_10[cache_size=0.1,treshold=0.5] |
0.000999978 |
-0.000888862 |
0.000288878 |
0.000555544 |
| LR_10[cache_size=0.1,treshold=0.6] |
0.000555523 |
-0.000888862 |
-2.22221e-05 |
0.000111109 |
| LR_10[cache_size=0.1,treshold=0.7] |
0.000777735 |
-0.00099997 |
-2.22259e-05 |
0.000111105 |
| LR_10[cache_size=0.1,treshold=0.8] |
0.000111109 |
-0.000111105 |
2.22218e-05 |
0 |
| LR_10[cache_size=0.1,treshold=0.9] |
0.000111109 |
-0.000111109 |
-2.22209e-05 |
0 |
| LR_11[cache_size=0.1,treshold=0.3] |
0.000777733 |
-0.00211105 |
0.000111102 |
0.00066663 |
| LR_11[cache_size=0.1,treshold=0.5] |
0.000999978 |
-0.00099997 |
0.000266657 |
0.000555544 |
| LR_11[cache_size=0.1,treshold=0.6] |
0.000444435 |
-0.000888862 |
-4.4443e-05 |
0.000111109 |
| LR_11[cache_size=0.1,treshold=0.7] |
0.000777735 |
-0.00099997 |
-2.22259e-05 |
0.000111105 |
| LR_11[cache_size=0.1,treshold=0.8] |
0.000111109 |
-0.000111105 |
2.22218e-05 |
0 |
| LR_11[cache_size=0.1,treshold=0.9] |
0.000111109 |
-0.000111109 |
-2.22209e-05 |
0 |
| LR_12[cache_size=0.1,treshold=0.3] |
0.000777762 |
-0.00211105 |
0.000133324 |
0.000666628 |
| LR_12[cache_size=0.1,treshold=0.5] |
0.000999978 |
-0.00099997 |
0.000266657 |
0.000555544 |
| LR_12[cache_size=0.1,treshold=0.6] |
0.000555523 |
-0.000888862 |
-6.66656e-05 |
0 |
| LR_12[cache_size=0.1,treshold=0.7] |
0.000777735 |
-0.00111108 |
-3.13551e-09 |
0 |
| LR_12[cache_size=0.1,treshold=0.8] |
0.000111105 |
-0.000111109 |
-2.22217e-05 |
0 |
| LR_12[cache_size=0.1,treshold=0.9] |
0.000111109 |
-0.000111109 |
-2.22209e-05 |
0 |
| LR_13[cache_size=0.1,treshold=0.3] |
0.00122215 |
-0.00222216 |
6.66594e-05 |
0.000333327 |
| LR_13[cache_size=0.1,treshold=0.5] |
0.00133326 |
-0.000777754 |
0.000399985 |
0.000777762 |
| LR_13[cache_size=0.1,treshold=0.6] |
0.00111109 |
-0.00099997 |
0.000355539 |
0.00044442 |
| LR_13[cache_size=0.1,treshold=0.7] |
0.000555525 |
-0.00233326 |
-0.000511093 |
0 |
| LR_13[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.1,treshold=0.3] |
0.00122215 |
-0.00222216 |
8.88804e-05 |
0.000333327 |
| LR_14[cache_size=0.1,treshold=0.5] |
0.00111105 |
-0.000777754 |
0.000355543 |
0.000666653 |
| LR_14[cache_size=0.1,treshold=0.6] |
0.0012222 |
-0.000666647 |
0.000399981 |
0.000555525 |
| LR_14[cache_size=0.1,treshold=0.7] |
0.000777735 |
-0.00233326 |
-0.000333324 |
0.000111109 |
| LR_14[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.1,treshold=0.3] |
0.00122215 |
-0.00222216 |
8.88804e-05 |
0.000333327 |
| LR_15[cache_size=0.1,treshold=0.5] |
0.00111105 |
-0.000777754 |
0.000355543 |
0.000666653 |
| LR_15[cache_size=0.1,treshold=0.6] |
0.0012222 |
-0.000777754 |
0.00037776 |
0.000555525 |
| LR_15[cache_size=0.1,treshold=0.7] |
0.00066663 |
-0.00222216 |
-0.000333324 |
0.000111109 |
| LR_15[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_1[cache_size=0.1,treshold=0.5] |
0.00077776 |
-0.00111108 |
0.000111108 |
0.00022221 |
| LR_1_log[cache_size=0.1,treshold=0.5] |
0.00133326 |
-0.000888862 |
0.000399982 |
0.000222218 |
| LR_1_mean[cache_size=0.1,treshold=0.5] |
0.00133326 |
-0.00099997 |
0.000355539 |
0.000111109 |
| LR_1_robust_scaler[cache_size=0.1,treshold=0.5] |
0.000666652 |
-0.00111108 |
8.88858e-05 |
0.00022221 |
| LR_1_std_scaler[cache_size=0.1,treshold=0.5] |
0.000666652 |
-0.00111108 |
8.88858e-05 |
0.00022221 |
| LR_2[cache_size=0.1,treshold=0.5] |
0.000555543 |
-0.00122219 |
4.44425e-05 |
0.000333314 |
| LR_2_log[cache_size=0.1,treshold=0.5] |
0.0012222 |
-0.000777754 |
0.000533309 |
0.000777735 |
| LR_2_mean[cache_size=0.1,treshold=0.5] |
0.0012222 |
-0.000777754 |
0.000511088 |
0.00066663 |
| LR_3[cache_size=0.1,treshold=0.5] |
0.000555543 |
-0.00111108 |
4.44422e-05 |
0.000333314 |
| LR_3_log[cache_size=0.1,treshold=0.5] |
0.00133326 |
-0.000777754 |
0.000533309 |
0.00066663 |
| LR_3_mean[cache_size=0.1,treshold=0.5] |
0.0013333 |
-0.000777754 |
0.000555532 |
0.00066663 |
| LR_4[cache_size=0.1,treshold=0.5] |
0.000666652 |
-0.00111108 |
6.66631e-05 |
0.000222218 |
| LR_4_log[cache_size=0.1,treshold=0.5] |
0.00133326 |
-0.00099997 |
0.000355541 |
0.000666653 |
| LR_4_mean[cache_size=0.1,treshold=0.5] |
0.00133326 |
-0.00099997 |
0.000288877 |
0.000444436 |
| LR_4_robust_scaler[cache_size=0.1,treshold=0.5] |
0.000666652 |
-0.00111108 |
6.66631e-05 |
0.000222218 |
| LR_4_std_scaler[cache_size=0.1,treshold=0.5] |
0.000666652 |
-0.00111108 |
6.66631e-05 |
0.000222218 |
| LR_5[cache_size=0.1,treshold=0.5] |
0.000666652 |
-0.00111108 |
6.66631e-05 |
0.000222218 |
| LR_5_imba[cache_size=0.1,treshold=0.5] |
0.000888869 |
-0.00177772 |
6.66603e-05 |
0.000333315 |
| LR_6[cache_size=0.1,treshold=0.5] |
0.000666652 |
-0.00111108 |
6.66631e-05 |
0.000222218 |
| LR_6_imba[cache_size=0.1,treshold=0.5] |
0.000888869 |
-0.00177772 |
6.66603e-05 |
0.000333315 |
| LR_7[cache_size=0.1,treshold=0.3] |
0.000777733 |
-0.00211105 |
8.88807e-05 |
0.00066663 |
| LR_7[cache_size=0.1,treshold=0.5] |
0.0013333 |
-0.000888862 |
0.000399983 |
0.000222218 |
| LR_7[cache_size=0.1,treshold=0.6] |
0.000666652 |
-0.00099997 |
-1.65414e-09 |
0 |
| LR_7[cache_size=0.1,treshold=0.7] |
0.00066663 |
-0.00155551 |
-0.000155551 |
0.000111109 |
| LR_7[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.1,treshold=0.3] |
0.00111105 |
-0.00211105 |
0.000133322 |
0.000555543 |
| LR_8[cache_size=0.1,treshold=0.5] |
0.0013333 |
-0.000888862 |
0.000511088 |
0.000555525 |
| LR_8[cache_size=0.1,treshold=0.6] |
0.00077776 |
-0.00099997 |
0.000111107 |
0.000333314 |
| LR_8[cache_size=0.1,treshold=0.7] |
0.000999946 |
-0.000666647 |
0.000111102 |
0.000111105 |
| LR_8[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.1,treshold=0.3] |
0.00111105 |
-0.00211105 |
0.000155543 |
0.00066663 |
| LR_9[cache_size=0.1,treshold=0.5] |
0.0012222 |
-0.000666647 |
0.00053331 |
0.000555525 |
| LR_9[cache_size=0.1,treshold=0.6] |
0.000888869 |
-0.00111108 |
0.000133328 |
0.000333314 |
| LR_9[cache_size=0.1,treshold=0.7] |
0.000999946 |
-0.000777754 |
8.88818e-05 |
0 |
| LR_9[cache_size=0.1,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.1,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.2,treshold=0.3] |
0.00349909 |
-0.00424912 |
-0.000724897 |
-0.000124961 |
| LR_10[cache_size=0.2,treshold=0.5] |
0.00149954 |
-0.00312436 |
-0.000449951 |
0.000249922 |
| LR_10[cache_size=0.2,treshold=0.6] |
0.00299907 |
-0.00299938 |
-8.26455e-08 |
0.000249922 |
| LR_10[cache_size=0.2,treshold=0.7] |
0.00149954 |
-0.00112477 |
0.000349862 |
0.000374903 |
| LR_10[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.2,treshold=0.3] |
0.00349909 |
-0.00424912 |
-0.00074989 |
-0.000124961 |
| LR_11[cache_size=0.2,treshold=0.5] |
0.0016245 |
-0.00274943 |
-0.000324982 |
0.000374883 |
| LR_11[cache_size=0.2,treshold=0.6] |
0.00274915 |
-0.00312436 |
-7.50634e-05 |
0.000374883 |
| LR_11[cache_size=0.2,treshold=0.7] |
0.00149954 |
-0.00124974 |
0.000324872 |
0.000749805 |
| LR_11[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_11[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.2,treshold=0.3] |
0.00349909 |
-0.00412415 |
-0.000749887 |
-0.000249923 |
| LR_12[cache_size=0.2,treshold=0.5] |
0.00137464 |
-0.00262446 |
-0.000324979 |
0.000499844 |
| LR_12[cache_size=0.2,treshold=0.6] |
0.00274915 |
-0.00312436 |
-2.50753e-05 |
0.000374883 |
| LR_12[cache_size=0.2,treshold=0.7] |
0.00137458 |
-0.000999794 |
0.000374866 |
0.000749805 |
| LR_12[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_12[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.2,treshold=0.3] |
0.00324916 |
-0.00487399 |
-0.00092486 |
0 |
| LR_13[cache_size=0.2,treshold=0.5] |
0.00124968 |
-0.00324933 |
-0.000624897 |
-0.000124961 |
| LR_13[cache_size=0.2,treshold=0.6] |
0.00174946 |
-0.00262446 |
-0.000524918 |
-0.000374883 |
| LR_13[cache_size=0.2,treshold=0.7] |
0.00087473 |
-0.000249948 |
0.000324899 |
0.000374883 |
| LR_13[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_13[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.2,treshold=0.3] |
0.00324916 |
-0.00487399 |
-0.00092486 |
0 |
| LR_14[cache_size=0.2,treshold=0.5] |
0.00124968 |
-0.00324933 |
-0.00064989 |
-0.000124961 |
| LR_14[cache_size=0.2,treshold=0.6] |
0.00174946 |
-0.00262446 |
-0.000399954 |
0 |
| LR_14[cache_size=0.2,treshold=0.7] |
0.000749805 |
-0.000374918 |
0.000249918 |
0.000374883 |
| LR_14[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_14[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.2,treshold=0.3] |
0.00324916 |
-0.00487399 |
-0.000874876 |
0.000124961 |
| LR_15[cache_size=0.2,treshold=0.5] |
0.00137464 |
-0.0033743 |
-0.000699878 |
-0.000249922 |
| LR_15[cache_size=0.2,treshold=0.6] |
0.0016245 |
-0.00262446 |
-0.000449938 |
-0.000124961 |
| LR_15[cache_size=0.2,treshold=0.7] |
0.000874773 |
-0.000374918 |
0.000174943 |
0 |
| LR_15[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_15[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_1[cache_size=0.2,treshold=0.5] |
0.00212434 |
-0.00287441 |
-0.000274988 |
-0.000499844 |
| LR_1_log[cache_size=0.2,treshold=0.5] |
0.00187451 |
-0.00324933 |
-0.000374966 |
-0.000374883 |
| LR_1_mean[cache_size=0.2,treshold=0.5] |
0.00199948 |
-0.00324933 |
-0.000349968 |
-0.000374883 |
| LR_1_robust_scaler[cache_size=0.2,treshold=0.5] |
0.00224931 |
-0.00287441 |
-0.000249996 |
-0.000499844 |
| LR_1_std_scaler[cache_size=0.2,treshold=0.5] |
0.00224931 |
-0.00287441 |
-0.000249996 |
-0.000499844 |
| LR_2[cache_size=0.2,treshold=0.5] |
0.00212434 |
-0.00287441 |
-0.000399959 |
-0.000499844 |
| LR_2_log[cache_size=0.2,treshold=0.5] |
0.00199948 |
-0.00324933 |
-0.000374967 |
-0.000374883 |
| LR_2_mean[cache_size=0.2,treshold=0.5] |
0.00187451 |
-0.00299938 |
-0.000399955 |
-0.000374883 |
| LR_3[cache_size=0.2,treshold=0.5] |
0.00199938 |
-0.00299938 |
-0.000424951 |
-0.000499844 |
| LR_3_log[cache_size=0.2,treshold=0.5] |
0.00199948 |
-0.00324933 |
-0.000399962 |
-0.000249922 |
| LR_3_mean[cache_size=0.2,treshold=0.5] |
0.00199948 |
-0.00324933 |
-0.000424954 |
-0.000374883 |
| LR_4[cache_size=0.2,treshold=0.5] |
0.00262419 |
-0.00274943 |
-0.000100038 |
-0.000749766 |
| LR_4_log[cache_size=0.2,treshold=0.5] |
0.00212445 |
-0.0038742 |
-0.00052493 |
-0.000124961 |
| LR_4_mean[cache_size=0.2,treshold=0.5] |
0.00174955 |
-0.00362425 |
-0.000624907 |
0 |
| LR_4_robust_scaler[cache_size=0.2,treshold=0.5] |
0.00262419 |
-0.00274943 |
-7.50445e-05 |
-0.000624805 |
| LR_4_std_scaler[cache_size=0.2,treshold=0.5] |
0.00262419 |
-0.00274943 |
-0.000100038 |
-0.000749766 |
| LR_5[cache_size=0.2,treshold=0.5] |
0.00262419 |
-0.00274943 |
-0.000100038 |
-0.000749766 |
| LR_5_imba[cache_size=0.2,treshold=0.5] |
0.00287425 |
-0.0041241 |
-0.000599944 |
0.000499846 |
| LR_6[cache_size=0.2,treshold=0.5] |
0.00262419 |
-0.00274943 |
-7.50432e-05 |
-0.000749766 |
| LR_6_imba[cache_size=0.2,treshold=0.5] |
0.00287425 |
-0.00424907 |
-0.000624936 |
0.000499846 |
| LR_7[cache_size=0.2,treshold=0.3] |
0.00374903 |
-0.00512394 |
-0.000899861 |
0 |
| LR_7[cache_size=0.2,treshold=0.5] |
0.00174955 |
-0.0033743 |
-0.000449947 |
-0.000374883 |
| LR_7[cache_size=0.2,treshold=0.6] |
0.00187442 |
-0.00212456 |
-0.000274984 |
0.000124961 |
| LR_7[cache_size=0.2,treshold=0.7] |
0.0016245 |
-0.00149969 |
0.000174909 |
0.000124968 |
| LR_7[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_7[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.2,treshold=0.3] |
0.00362406 |
-0.00512394 |
-0.000899862 |
0.000249923 |
| LR_8[cache_size=0.2,treshold=0.5] |
0.00187451 |
-0.0033743 |
-0.000449946 |
-0.000249922 |
| LR_8[cache_size=0.2,treshold=0.6] |
0.00174946 |
-0.00224954 |
-0.000349965 |
0.000124961 |
| LR_8[cache_size=0.2,treshold=0.7] |
0.00124961 |
-0.00137472 |
0.000199907 |
0.000249935 |
| LR_8[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.2,treshold=0.3] |
0.00362406 |
-0.00512394 |
-0.000949849 |
0.000124961 |
| LR_9[cache_size=0.2,treshold=0.5] |
0.00199948 |
-0.0033743 |
-0.00039996 |
-0.000249922 |
| LR_9[cache_size=0.2,treshold=0.6] |
0.00174946 |
-0.00224954 |
-0.00032497 |
0.000124961 |
| LR_9[cache_size=0.2,treshold=0.7] |
0.00112465 |
-0.00137472 |
0.000174917 |
0.000249935 |
| LR_9[cache_size=0.2,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.2,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_10[cache_size=0.4,treshold=0.3] |
0.0071554 |
-0.000665599 |
0.00256262 |
0.00199709 |
| LR_10[cache_size=0.4,treshold=0.5] |
0.00532482 |
0 |
0.00203006 |
0.000831999 |
| LR_10[cache_size=0.4,treshold=0.6] |
0.00632323 |
-0.00282888 |
0.00189691 |
0.0013312 |
| LR_10[cache_size=0.4,treshold=0.7] |
0.00482562 |
-0.00183031 |
0.000698878 |
-0.000499272 |
| LR_10[cache_size=0.4,treshold=0.8] |
0.000166405 |
-0.000166424 |
-2.16048e-09 |
0 |
| LR_10[cache_size=0.4,treshold=0.9] |
0.000166401 |
-0.000166405 |
-6.65592e-05 |
-0.000166392 |
| LR_11[cache_size=0.4,treshold=0.3] |
0.00832023 |
-0.0004992 |
0.00279559 |
0.00216351 |
| LR_11[cache_size=0.4,treshold=0.5] |
0.00515842 |
-0.000166424 |
0.00186365 |
0.0004992 |
| LR_11[cache_size=0.4,treshold=0.6] |
0.00648963 |
-0.00332809 |
0.00178043 |
0.001664 |
| LR_11[cache_size=0.4,treshold=0.7] |
0.00565762 |
-0.00183066 |
0.000765402 |
-0.00099839 |
| LR_11[cache_size=0.4,treshold=0.8] |
0 |
-0.0001664 |
-6.65584e-05 |
0 |
| LR_11[cache_size=0.4,treshold=0.9] |
0 |
-0.000166392 |
-3.32784e-05 |
0 |
| LR_12[cache_size=0.4,treshold=0.3] |
0.00782102 |
-0.0013312 |
0.00252935 |
0.00216351 |
| LR_12[cache_size=0.4,treshold=0.5] |
0.00515842 |
-0.000166424 |
0.00189693 |
0.000665599 |
| LR_12[cache_size=0.4,treshold=0.6] |
0.00665603 |
-0.00316169 |
0.00183036 |
0.0013312 |
| LR_12[cache_size=0.4,treshold=0.7] |
0.00549122 |
-0.00232994 |
0.000632267 |
-0.000499214 |
| LR_12[cache_size=0.4,treshold=0.8] |
0 |
-0.0001664 |
-6.65584e-05 |
0 |
| LR_12[cache_size=0.4,treshold=0.9] |
0 |
-0.000166392 |
-3.32784e-05 |
0 |
| LR_13[cache_size=0.4,treshold=0.3] |
0.0063229 |
-0.0003328 |
0.00262909 |
0.00149761 |
| LR_13[cache_size=0.4,treshold=0.5] |
0.00482562 |
-0.002496 |
0.00159748 |
0.00116474 |
| LR_13[cache_size=0.4,treshold=0.6] |
0.00582402 |
-0.00199685 |
0.00206336 |
0.00166424 |
| LR_13[cache_size=0.4,treshold=0.7] |
0.00482562 |
-0.00282888 |
-0.000232996 |
-0.00149782 |
| LR_13[cache_size=0.4,treshold=0.8] |
0.000166401 |
-0.0001664 |
-3.32783e-05 |
0 |
| LR_13[cache_size=0.4,treshold=0.9] |
0.000166401 |
-0.000166392 |
1.71664e-09 |
0 |
| LR_14[cache_size=0.4,treshold=0.3] |
0.0063229 |
-0.0003328 |
0.00266237 |
0.00166401 |
| LR_14[cache_size=0.4,treshold=0.5] |
0.00482562 |
-0.0026624 |
0.0015642 |
0.00116474 |
| LR_14[cache_size=0.4,treshold=0.6] |
0.00599043 |
-0.00183045 |
0.0021632 |
0.00166424 |
| LR_14[cache_size=0.4,treshold=0.7] |
0.00499202 |
-0.00249607 |
-3.33202e-05 |
-0.00166424 |
| LR_14[cache_size=0.4,treshold=0.8] |
0.000166401 |
0 |
3.32801e-05 |
0 |
| LR_14[cache_size=0.4,treshold=0.9] |
0.000166401 |
-0.000166392 |
1.71664e-09 |
0 |
| LR_15[cache_size=0.4,treshold=0.3] |
0.00665568 |
-0.0004992 |
0.0027955 |
0.00166401 |
| LR_15[cache_size=0.4,treshold=0.5] |
0.00482562 |
-0.002496 |
0.00163076 |
0.00133114 |
| LR_15[cache_size=0.4,treshold=0.6] |
0.00582402 |
-0.00183045 |
0.00203009 |
0.00183066 |
| LR_15[cache_size=0.4,treshold=0.7] |
0.00449282 |
-0.00232966 |
-2.05505e-08 |
-0.000998544 |
| LR_15[cache_size=0.4,treshold=0.8] |
0.000166401 |
-0.000166392 |
1.71664e-09 |
0 |
| LR_15[cache_size=0.4,treshold=0.9] |
0.000166401 |
-0.000166392 |
1.71664e-09 |
0 |
| LR_1[cache_size=0.4,treshold=0.5] |
0.00648963 |
-0.00316169 |
0.00199672 |
0.000831999 |
| LR_1_log[cache_size=0.4,treshold=0.5] |
0.00482562 |
-0.0044928 |
0.00116485 |
0.00083212 |
| LR_1_mean[cache_size=0.4,treshold=0.5] |
0.00549122 |
-0.0038272 |
0.00229641 |
0.00282921 |
| LR_1_robust_scaler[cache_size=0.4,treshold=0.5] |
0.00632323 |
-0.00299528 |
0.00203001 |
0.000831999 |
| LR_1_std_scaler[cache_size=0.4,treshold=0.5] |
0.00632323 |
-0.00316169 |
0.00199673 |
0.000831999 |
| LR_2[cache_size=0.4,treshold=0.5] |
0.00698883 |
-0.0034945 |
0.00196344 |
0.0003328 |
| LR_2_log[cache_size=0.4,treshold=0.5] |
0.00482562 |
-0.0043264 |
0.00126468 |
0.000665696 |
| LR_2_mean[cache_size=0.4,treshold=0.5] |
0.00515842 |
-0.0044928 |
0.00149765 |
0.00116474 |
| LR_3[cache_size=0.4,treshold=0.5] |
0.00698883 |
-0.00332809 |
0.00199672 |
0.0003328 |
| LR_3_log[cache_size=0.4,treshold=0.5] |
0.00482562 |
-0.00416 |
0.00133125 |
0.00083212 |
| LR_3_mean[cache_size=0.4,treshold=0.5] |
0.00532482 |
-0.00416 |
0.00156421 |
0.000998353 |
| LR_4[cache_size=0.4,treshold=0.5] |
0.00449282 |
-0.000665618 |
0.00236287 |
0.0026624 |
| LR_4_log[cache_size=0.4,treshold=0.5] |
0.00515842 |
-0.0023296 |
0.00176393 |
0.00232994 |
| LR_4_mean[cache_size=0.4,treshold=0.5] |
0.00482562 |
-0.0028288 |
0.00176391 |
0.00166424 |
| LR_4_robust_scaler[cache_size=0.4,treshold=0.5] |
0.00465922 |
-0.000832023 |
0.00236287 |
0.0026624 |
| LR_4_std_scaler[cache_size=0.4,treshold=0.5] |
0.00465922 |
-0.000832023 |
0.00232959 |
0.002496 |
| LR_5[cache_size=0.4,treshold=0.5] |
0.00465922 |
-0.000832023 |
0.00236287 |
0.0026624 |
| LR_5_imba[cache_size=0.4,treshold=0.5] |
0.00648978 |
-0.002496 |
0.00356109 |
0.00432702 |
| LR_6[cache_size=0.4,treshold=0.5] |
0.00465922 |
-0.000832023 |
0.00236287 |
0.0026624 |
| LR_6_imba[cache_size=0.4,treshold=0.5] |
0.00648978 |
-0.0021632 |
0.00366093 |
0.00432702 |
| LR_7[cache_size=0.4,treshold=0.3] |
0.00815321 |
-0.00116497 |
0.00292857 |
0.000665599 |
| LR_7[cache_size=0.4,treshold=0.5] |
0.00482562 |
-0.0031616 |
0.00183046 |
0.00149782 |
| LR_7[cache_size=0.4,treshold=0.6] |
0.00615683 |
-0.00183045 |
0.00222974 |
0.00133139 |
| LR_7[cache_size=0.4,treshold=0.7] |
0.0004992 |
-0.000332809 |
6.65599e-05 |
0 |
| LR_7[cache_size=0.4,treshold=0.8] |
0.000332801 |
-0.000166405 |
9.41326e-10 |
0 |
| LR_7[cache_size=0.4,treshold=0.9] |
0.000332801 |
-0.000166405 |
3.32809e-05 |
0 |
| LR_8[cache_size=0.4,treshold=0.3] |
0.00865239 |
-0.00133139 |
0.00309496 |
0.00149761 |
| LR_8[cache_size=0.4,treshold=0.5] |
0.00499214 |
-0.003328 |
0.00186373 |
0.00166392 |
| LR_8[cache_size=0.4,treshold=0.6] |
0.00615683 |
-0.00149764 |
0.00246271 |
0.00149782 |
| LR_8[cache_size=0.4,treshold=0.7] |
0.0003328 |
-0.000166405 |
6.09054e-10 |
0 |
| LR_8[cache_size=0.4,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_8[cache_size=0.4,treshold=0.9] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.4,treshold=0.3] |
0.00865239 |
-0.00133139 |
0.00306168 |
0.0011648 |
| LR_9[cache_size=0.4,treshold=0.5] |
0.00515854 |
-0.003328 |
0.00183044 |
0.00166392 |
| LR_9[cache_size=0.4,treshold=0.6] |
0.00615683 |
-0.00166405 |
0.00242942 |
0.00116497 |
| LR_9[cache_size=0.4,treshold=0.7] |
0.0003328 |
-0.000166424 |
-3.32842e-05 |
-0.000166392 |
| LR_9[cache_size=0.4,treshold=0.8] |
0 |
0 |
0 |
0 |
| LR_9[cache_size=0.4,treshold=0.9] |
0 |
0 |
0 |
0 |
| Offline Clock 1st iteration |
0 |
0 |
0 |
0 |
| Offline Clock 2nd iteration |
9.81851 |
0.0001001 |
2.73143 |
0.859981 |
| Zipf Optimal Distribution |
0.00682239 |
-0.00499176 |
0.000561115 |
0.000101012 |
Model Summaries Plot
Miss Ratio Reduced (%)
Cache Size All
Cache Size 0.001
Cache Size 0.01
Cache Size 0.1
Cache Size 0.2
Cache Size 0.4
Model Classification Report
LR_10_0.001
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9369647659656092
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9369647659656092
LR_10_0.01
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.63 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.947614194606559
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.63 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.947614194606559
LR_10_0.1
precision recall f1-score support
0 0.41 0.57 0.48 8019514
1 0.91 0.85 0.88 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.68 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.8026812240957527
precision recall f1-score support
0 0.41 0.57 0.48 8019514
1 0.91 0.85 0.88 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.68 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.8026812240957527
LR_10_0.2
precision recall f1-score support
0 0.55 0.59 0.57 25620627
1 0.85 0.83 0.84 73187446
accuracy 0.77 98808073
macro avg 0.70 0.71 0.70 98808073
weighted avg 0.77 0.77 0.77 98808073
Accuracy: 0.7659223351112211
precision recall f1-score support
0 0.55 0.59 0.57 25620627
1 0.85 0.83 0.84 73187446
accuracy 0.77 98808073
macro avg 0.70 0.71 0.70 98808073
weighted avg 0.77 0.77 0.77 98808073
Accuracy: 0.7659223351112211
LR_10_0.4
precision recall f1-score support
0 0.62 0.68 0.65 66028440
1 0.78 0.73 0.75 103663142
accuracy 0.71 169691582
macro avg 0.70 0.71 0.70 169691582
weighted avg 0.72 0.71 0.71 169691582
Accuracy: 0.7110567924341704
precision recall f1-score support
0 0.62 0.68 0.65 66028440
1 0.78 0.73 0.75 103663142
accuracy 0.71 169691582
macro avg 0.70 0.71 0.70 169691582
weighted avg 0.72 0.71 0.71 169691582
Accuracy: 0.7110567924341704
LR_10_All
precision recall f1-score support
0 0.40 0.70 0.50 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.61 0.57 324953889
weighted avg 0.67 0.58 0.60 324953889
Accuracy: 0.5798402800466254
precision recall f1-score support
0 0.40 0.70 0.50 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.61 0.57 324953889
weighted avg 0.67 0.58 0.60 324953889
Accuracy: 0.5798402800466254
LR_11_0.001
precision recall f1-score support
0 0.01 0.66 0.01 1026
1 1.00 0.75 0.86 499456
accuracy 0.75 500482
macro avg 0.50 0.71 0.43 500482
weighted avg 1.00 0.75 0.86 500482
Accuracy: 0.752214864870265
precision recall f1-score support
0 0.01 0.66 0.01 1026
1 1.00 0.75 0.86 499456
accuracy 0.75 500482
macro avg 0.50 0.71 0.43 500482
weighted avg 1.00 0.75 0.86 500482
Accuracy: 0.752214864870265
LR_11_0.01
precision recall f1-score support
0 0.06 0.59 0.11 98473
1 0.99 0.81 0.89 4925407
accuracy 0.81 5023880
macro avg 0.53 0.70 0.50 5023880
weighted avg 0.97 0.81 0.88 5023880
Accuracy: 0.8104256072995374
precision recall f1-score support
0 0.06 0.59 0.11 98473
1 0.99 0.81 0.89 4925407
accuracy 0.81 5023880
macro avg 0.53 0.70 0.50 5023880
weighted avg 0.97 0.81 0.88 5023880
Accuracy: 0.8104256072995374
LR_11_0.1
precision recall f1-score support
0 0.41 0.57 0.47 8019514
1 0.91 0.84 0.88 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.68 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.8009982235965565
precision recall f1-score support
0 0.41 0.57 0.47 8019514
1 0.91 0.84 0.88 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.68 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.8009982235965565
LR_11_0.2
precision recall f1-score support
0 0.55 0.59 0.57 25620627
1 0.85 0.83 0.84 73187446
accuracy 0.77 98808073
macro avg 0.70 0.71 0.70 98808073
weighted avg 0.77 0.77 0.77 98808073
Accuracy: 0.767724131205352
precision recall f1-score support
0 0.55 0.59 0.57 25620627
1 0.85 0.83 0.84 73187446
accuracy 0.77 98808073
macro avg 0.70 0.71 0.70 98808073
weighted avg 0.77 0.77 0.77 98808073
Accuracy: 0.767724131205352
LR_11_0.4
precision recall f1-score support
0 0.62 0.68 0.65 66028440
1 0.78 0.73 0.75 103663142
accuracy 0.71 169691582
macro avg 0.70 0.71 0.70 169691582
weighted avg 0.72 0.71 0.71 169691582
Accuracy: 0.7109879911426602
precision recall f1-score support
0 0.62 0.68 0.65 66028440
1 0.78 0.73 0.75 103663142
accuracy 0.71 169691582
macro avg 0.70 0.71 0.70 169691582
weighted avg 0.72 0.71 0.71 169691582
Accuracy: 0.7109998774128937
LR_11_All
precision recall f1-score support
0 0.39 0.70 0.50 99768080
1 0.80 0.53 0.63 225185809
accuracy 0.58 324953889
macro avg 0.60 0.61 0.57 324953889
weighted avg 0.67 0.58 0.59 324953889
Accuracy: 0.5788021666052441
precision recall f1-score support
0 0.39 0.70 0.50 99768080
1 0.80 0.53 0.63 225185809
accuracy 0.58 324953889
macro avg 0.60 0.61 0.57 324953889
weighted avg 0.67 0.58 0.59 324953889
Accuracy: 0.5788021666052441
LR_12_0.001
precision recall f1-score support
0 0.01 0.61 0.02 1026
1 1.00 0.85 0.92 499456
accuracy 0.85 500482
macro avg 0.50 0.73 0.47 500482
weighted avg 1.00 0.85 0.92 500482
Accuracy: 0.8518348312227013
precision recall f1-score support
0 0.01 0.61 0.02 1026
1 1.00 0.85 0.92 499456
accuracy 0.85 500482
macro avg 0.50 0.73 0.47 500482
weighted avg 1.00 0.85 0.92 500482
Accuracy: 0.8518348312227013
LR_12_0.01
precision recall f1-score support
0 0.07 0.57 0.13 98473
1 0.99 0.85 0.92 4925407
accuracy 0.85 5023880
macro avg 0.53 0.71 0.52 5023880
weighted avg 0.97 0.85 0.90 5023880
Accuracy: 0.84876191310302
precision recall f1-score support
0 0.07 0.57 0.13 98473
1 0.99 0.85 0.92 4925407
accuracy 0.85 5023880
macro avg 0.53 0.71 0.52 5023880
weighted avg 0.97 0.85 0.90 5023880
Accuracy: 0.84876191310302
LR_12_0.1
precision recall f1-score support
0 0.41 0.57 0.48 8019514
1 0.91 0.85 0.88 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.68 50929872
weighted avg 0.83 0.80 0.82 50929872
Accuracy: 0.8031211034655653
precision recall f1-score support
0 0.41 0.57 0.48 8019514
1 0.91 0.85 0.88 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.68 50929872
weighted avg 0.83 0.80 0.82 50929872
Accuracy: 0.8031211034655653
LR_12_0.2
precision recall f1-score support
0 0.55 0.58 0.57 25620627
1 0.85 0.83 0.84 73187446
accuracy 0.77 98808073
macro avg 0.70 0.71 0.71 98808073
weighted avg 0.77 0.77 0.77 98808073
Accuracy: 0.7696034412086956
precision recall f1-score support
0 0.55 0.58 0.57 25620627
1 0.85 0.83 0.84 73187446
accuracy 0.77 98808073
macro avg 0.70 0.71 0.71 98808073
weighted avg 0.77 0.77 0.77 98808073
Accuracy: 0.7696034412086956
LR_12_0.4
precision recall f1-score support
0 0.62 0.68 0.65 66028440
1 0.78 0.73 0.75 103663142
accuracy 0.71 169691582
macro avg 0.70 0.71 0.70 169691582
weighted avg 0.72 0.71 0.71 169691582
Accuracy: 0.7110399618998189
precision recall f1-score support
0 0.62 0.68 0.65 66028440
1 0.78 0.73 0.75 103663142
accuracy 0.71 169691582
macro avg 0.70 0.71 0.70 169691582
weighted avg 0.72 0.71 0.71 169691582
Accuracy: 0.7110399618998189
LR_12_All
precision recall f1-score support
0 0.39 0.70 0.50 99768080
1 0.80 0.53 0.63 225185809
accuracy 0.58 324953889
macro avg 0.60 0.61 0.57 324953889
weighted avg 0.67 0.58 0.59 324953889
Accuracy: 0.5785499215859515
precision recall f1-score support
0 0.39 0.70 0.50 99768080
1 0.80 0.53 0.63 225185809
accuracy 0.58 324953889
macro avg 0.60 0.61 0.57 324953889
weighted avg 0.67 0.58 0.59 324953889
Accuracy: 0.5785499215859515
LR_13_0.001
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9365531627511079
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9365531627511079
LR_13_0.01
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.63 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.9475303948342715
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.63 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.9475303948342715
LR_13_0.1
precision recall f1-score support
0 0.42 0.56 0.48 8019514
1 0.91 0.86 0.88 42910358
accuracy 0.81 50929872
macro avg 0.67 0.71 0.68 50929872
weighted avg 0.84 0.81 0.82 50929872
Accuracy: 0.8108006829469353
precision recall f1-score support
0 0.42 0.56 0.48 8019514
1 0.91 0.86 0.88 42910358
accuracy 0.81 50929872
macro avg 0.67 0.71 0.68 50929872
weighted avg 0.84 0.81 0.82 50929872
Accuracy: 0.8108006829469353
LR_13_0.2
precision recall f1-score support
0 0.53 0.60 0.56 25620627
1 0.85 0.81 0.83 73187446
accuracy 0.76 98808073
macro avg 0.69 0.71 0.70 98808073
weighted avg 0.77 0.76 0.76 98808073
Accuracy: 0.7579026260334011
precision recall f1-score support
0 0.53 0.60 0.56 25620627
1 0.85 0.81 0.83 73187446
accuracy 0.76 98808073
macro avg 0.69 0.71 0.70 98808073
weighted avg 0.77 0.76 0.76 98808073
Accuracy: 0.7579026260334011
LR_13_0.4
precision recall f1-score support
0 0.65 0.65 0.65 66028440
1 0.78 0.78 0.78 103663142
accuracy 0.73 169691582
macro avg 0.71 0.71 0.71 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7285107696149594
precision recall f1-score support
0 0.65 0.65 0.65 66028440
1 0.78 0.78 0.78 103663142
accuracy 0.73 169691582
macro avg 0.71 0.71 0.71 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7285107696149594
LR_13_All
precision recall f1-score support
0 0.38 0.56 0.45 99768080
1 0.75 0.60 0.67 225185809
accuracy 0.59 324953889
macro avg 0.57 0.58 0.56 324953889
weighted avg 0.64 0.59 0.60 324953889
Accuracy: 0.5896379716815761
precision recall f1-score support
0 0.38 0.56 0.45 99768080
1 0.75 0.60 0.67 225185809
accuracy 0.59 324953889
macro avg 0.57 0.58 0.56 324953889
weighted avg 0.64 0.59 0.60 324953889
Accuracy: 0.5896379716815761
LR_14_0.001
precision recall f1-score support
0 0.01 0.66 0.01 1026
1 1.00 0.75 0.86 499456
accuracy 0.75 500482
macro avg 0.50 0.71 0.43 500482
weighted avg 1.00 0.75 0.86 500482
Accuracy: 0.752214864870265
precision recall f1-score support
0 0.01 0.66 0.01 1026
1 1.00 0.75 0.86 499456
accuracy 0.75 500482
macro avg 0.50 0.71 0.43 500482
weighted avg 1.00 0.75 0.86 500482
Accuracy: 0.752214864870265
LR_14_0.01
precision recall f1-score support
0 0.06 0.59 0.11 98473
1 0.99 0.82 0.90 4925407
accuracy 0.82 5023880
macro avg 0.53 0.71 0.51 5023880
weighted avg 0.97 0.82 0.88 5023880
Accuracy: 0.8189315827607347
precision recall f1-score support
0 0.06 0.59 0.11 98473
1 0.99 0.82 0.90 4925407
accuracy 0.82 5023880
macro avg 0.53 0.71 0.51 5023880
weighted avg 0.97 0.82 0.88 5023880
Accuracy: 0.8189315827607347
LR_14_0.1
precision recall f1-score support
0 0.40 0.57 0.47 8019514
1 0.91 0.84 0.88 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.67 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.7984757157842455
precision recall f1-score support
0 0.40 0.57 0.47 8019514
1 0.91 0.84 0.88 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.67 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.7984757157842455
LR_14_0.2
precision recall f1-score support
0 0.53 0.60 0.56 25620627
1 0.85 0.81 0.83 73187446
accuracy 0.76 98808073
macro avg 0.69 0.70 0.70 98808073
weighted avg 0.77 0.76 0.76 98808073
Accuracy: 0.7577006081274351
precision recall f1-score support
0 0.53 0.60 0.56 25620627
1 0.85 0.81 0.83 73187446
accuracy 0.76 98808073
macro avg 0.69 0.70 0.70 98808073
weighted avg 0.77 0.76 0.76 98808073
Accuracy: 0.7577006081274351
LR_14_0.4
precision recall f1-score support
0 0.65 0.65 0.65 66028440
1 0.78 0.78 0.78 103663142
accuracy 0.73 169691582
macro avg 0.71 0.71 0.71 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7285412602258609
precision recall f1-score support
0 0.65 0.65 0.65 66028440
1 0.78 0.78 0.78 103663142
accuracy 0.73 169691582
macro avg 0.71 0.71 0.71 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7285412602258609
LR_14_All
precision recall f1-score support
0 0.38 0.56 0.45 99768080
1 0.75 0.60 0.67 225185809
accuracy 0.59 324953889
macro avg 0.57 0.58 0.56 324953889
weighted avg 0.64 0.59 0.60 324953889
Accuracy: 0.5899010643937854
precision recall f1-score support
0 0.38 0.56 0.45 99768080
1 0.75 0.60 0.67 225185809
accuracy 0.59 324953889
macro avg 0.57 0.58 0.56 324953889
weighted avg 0.64 0.59 0.60 324953889
Accuracy: 0.5899010643937854
LR_15_0.001
precision recall f1-score support
0 0.01 0.61 0.02 1026
1 1.00 0.85 0.92 499456
accuracy 0.85 500482
macro avg 0.50 0.73 0.47 500482
weighted avg 1.00 0.85 0.92 500482
Accuracy: 0.8517648986377132
precision recall f1-score support
0 0.01 0.61 0.02 1026
1 1.00 0.85 0.92 499456
accuracy 0.85 500482
macro avg 0.50 0.73 0.47 500482
weighted avg 1.00 0.85 0.92 500482
Accuracy: 0.8517648986377132
LR_15_0.01
precision recall f1-score support
0 0.08 0.57 0.13 98473
1 0.99 0.86 0.92 4925407
accuracy 0.86 5023880
macro avg 0.53 0.72 0.53 5023880
weighted avg 0.97 0.86 0.91 5023880
Accuracy: 0.8553002858348527
precision recall f1-score support
0 0.08 0.57 0.13 98473
1 0.99 0.86 0.92 4925407
accuracy 0.86 5023880
macro avg 0.53 0.72 0.53 5023880
weighted avg 0.97 0.86 0.91 5023880
Accuracy: 0.8553002858348527
LR_15_0.1
precision recall f1-score support
0 0.40 0.57 0.47 8019514
1 0.91 0.84 0.88 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.67 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.7984756765145611
precision recall f1-score support
0 0.40 0.57 0.47 8019514
1 0.91 0.84 0.88 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.67 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.7984756765145611
LR_15_0.2
precision recall f1-score support
0 0.53 0.60 0.56 25620627
1 0.85 0.81 0.83 73187446
accuracy 0.76 98808073
macro avg 0.69 0.71 0.70 98808073
weighted avg 0.77 0.76 0.76 98808073
Accuracy: 0.7579156108023684
precision recall f1-score support
0 0.53 0.60 0.56 25620627
1 0.85 0.81 0.83 73187446
accuracy 0.76 98808073
macro avg 0.69 0.71 0.70 98808073
weighted avg 0.77 0.76 0.76 98808073
Accuracy: 0.7579156108023684
LR_15_0.4
precision recall f1-score support
0 0.65 0.65 0.65 66028440
1 0.78 0.78 0.78 103663142
accuracy 0.73 169691582
macro avg 0.71 0.71 0.71 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7285153249381575
precision recall f1-score support
0 0.65 0.65 0.65 66028440
1 0.78 0.78 0.78 103663142
accuracy 0.73 169691582
macro avg 0.71 0.71 0.71 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7285153249381575
LR_15_All
precision recall f1-score support
0 0.38 0.56 0.45 99768080
1 0.75 0.61 0.67 225185809
accuracy 0.59 324953889
macro avg 0.57 0.58 0.56 324953889
weighted avg 0.64 0.59 0.61 324953889
Accuracy: 0.5901402275570242
precision recall f1-score support
0 0.38 0.56 0.45 99768080
1 0.75 0.61 0.67 225185809
accuracy 0.59 324953889
macro avg 0.57 0.58 0.56 324953889
weighted avg 0.64 0.59 0.61 324953889
Accuracy: 0.5901402275570242
LR_1_0.001
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.6262642812328915
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.6262642812328915
LR_1_0.01
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.631169932402844
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.631169932402844
LR_1_0.1
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.64 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6419880065671478
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.64 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6419880065671478
LR_1_0.2
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.74 73187446
accuracy 0.66 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.66 0.68 98808073
Accuracy: 0.6571487635428331
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.74 73187446
accuracy 0.66 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.66 0.68 98808073
Accuracy: 0.6571487635428331
LR_1_0.4
precision recall f1-score support
0 0.59 0.72 0.65 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6925760053318378
precision recall f1-score support
0 0.59 0.72 0.65 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6925760053318378
LR_1_All
precision recall f1-score support
0 0.40 0.70 0.51 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.62 0.57 324953889
weighted avg 0.68 0.58 0.60 324953889
Accuracy: 0.5826247212569904
precision recall f1-score support
0 0.40 0.70 0.51 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.62 0.57 324953889
weighted avg 0.68 0.58 0.60 324953889
Accuracy: 0.5826247212569904
LR_1_log_0.001
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9369108179714755
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9369108179714755
LR_1_log_0.01
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.63 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.947614194606559
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.63 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.947614194606559
LR_1_log_0.1
precision recall f1-score support
0 0.38 0.58 0.46 8019514
1 0.91 0.83 0.87 42910358
accuracy 0.79 50929872
macro avg 0.65 0.70 0.66 50929872
weighted avg 0.83 0.79 0.80 50929872
Accuracy: 0.7870163702747967
precision recall f1-score support
0 0.38 0.58 0.46 8019514
1 0.91 0.83 0.87 42910358
accuracy 0.79 50929872
macro avg 0.65 0.70 0.66 50929872
weighted avg 0.83 0.79 0.80 50929872
Accuracy: 0.7870163702747967
LR_1_log_0.2
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.7429965565667899
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.7429965565667899
LR_1_log_0.4
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.73 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7347461997260418
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.73 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7347461997260418
LR_1_log_All
precision recall f1-score support
0 0.44 0.57 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.62 0.61 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.6456504264209622
precision recall f1-score support
0 0.44 0.57 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.62 0.61 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.6456504264209622
LR_1_mean_0.001
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9369747563348931
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9369747563348931
LR_1_mean_0.01
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.63 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.9476440520076116
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.63 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.9476440520076116
LR_1_mean_0.1
precision recall f1-score support
0 0.38 0.58 0.46 8019514
1 0.91 0.83 0.87 42910358
accuracy 0.79 50929872
macro avg 0.65 0.70 0.66 50929872
weighted avg 0.83 0.79 0.80 50929872
Accuracy: 0.7869054137815229
precision recall f1-score support
0 0.38 0.58 0.46 8019514
1 0.91 0.83 0.87 42910358
accuracy 0.79 50929872
macro avg 0.65 0.70 0.66 50929872
weighted avg 0.83 0.79 0.80 50929872
Accuracy: 0.7869054137815229
LR_1_mean_0.2
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.7427428627213487
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.7427428627213487
LR_1_mean_0.4
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.73 169691582
Accuracy: 0.7360563531077222
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.73 169691582
Accuracy: 0.7360563531077222
LR_1_mean_All
precision recall f1-score support
0 0.39 0.52 0.45 99768080
1 0.75 0.65 0.70 225185809
accuracy 0.61 324953889
macro avg 0.57 0.58 0.57 324953889
weighted avg 0.64 0.61 0.62 324953889
Accuracy: 0.60738761615498
precision recall f1-score support
0 0.39 0.52 0.45 99768080
1 0.75 0.65 0.70 225185809
accuracy 0.61 324953889
macro avg 0.57 0.58 0.57 324953889
weighted avg 0.64 0.61 0.62 324953889
Accuracy: 0.60738761615498
LR_1_robust_scaler_0.001
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.6262522927897507
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.6262522927897507
LR_1_robust_scaler_0.01
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6313144422239385
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6313144422239385
LR_1_robust_scaler_0.1
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.64 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6419735160536041
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.64 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6419735160536041
LR_1_robust_scaler_0.2
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.74 73187446
accuracy 0.66 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.66 0.68 98808073
Accuracy: 0.657163428336468
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.74 73187446
accuracy 0.66 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.66 0.68 98808073
Accuracy: 0.657163428336468
LR_1_robust_scaler_0.4
precision recall f1-score support
0 0.59 0.72 0.65 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6925738956219997
precision recall f1-score support
0 0.59 0.72 0.65 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6925738956219997
LR_1_robust_scaler_All
precision recall f1-score support
0 0.40 0.70 0.51 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.62 0.57 324953889
weighted avg 0.68 0.58 0.60 324953889
Accuracy: 0.5826195636021454
precision recall f1-score support
0 0.40 0.70 0.51 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.62 0.57 324953889
weighted avg 0.68 0.58 0.60 324953889
Accuracy: 0.5826195636021454
LR_1_std_scaler_0.001
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.626330217670166
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.626330217670166
LR_1_std_scaler_0.01
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6314165545355382
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6314165545355382
LR_1_std_scaler_0.1
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.64 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.64190860326529
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.64 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.64190860326529
LR_1_std_scaler_0.2
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.74 73187446
accuracy 0.66 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.66 0.68 98808073
Accuracy: 0.6571269738253067
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.74 73187446
accuracy 0.66 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.66 0.68 98808073
Accuracy: 0.6571269738253067
LR_1_std_scaler_0.4
precision recall f1-score support
0 0.59 0.72 0.65 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6925725048635589
precision recall f1-score support
0 0.59 0.72 0.65 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6925725048635589
LR_1_std_scaler_All
precision recall f1-score support
0 0.40 0.70 0.51 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.62 0.57 324953889
weighted avg 0.68 0.58 0.60 324953889
Accuracy: 0.5826236318716592
precision recall f1-score support
0 0.40 0.70 0.51 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.62 0.57 324953889
weighted avg 0.68 0.58 0.60 324953889
Accuracy: 0.5826236318716592
LR_2_0.001
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.6272553258658653
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.6272553258658653
LR_2_0.01
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.631165951416037
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.631165951416037
LR_2_0.1
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.64 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6419731822612866
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.64 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6419731822612866
LR_2_0.2
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.74 73187446
accuracy 0.66 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.66 0.68 98808073
Accuracy: 0.657124140048759
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.74 73187446
accuracy 0.66 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.66 0.68 98808073
Accuracy: 0.657124140048759
LR_2_0.4
precision recall f1-score support
0 0.59 0.72 0.65 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6925379539451757
precision recall f1-score support
0 0.59 0.72 0.65 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6925379539451757
LR_2_All
precision recall f1-score support
0 0.40 0.70 0.51 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.61 0.57 324953889
weighted avg 0.68 0.58 0.60 324953889
Accuracy: 0.5821473396799384
precision recall f1-score support
0 0.40 0.70 0.51 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.61 0.57 324953889
weighted avg 0.68 0.58 0.60 324953889
Accuracy: 0.5821473396799384
LR_2_log_0.001
precision recall f1-score support
0 0.01 0.62 0.02 1026
1 1.00 0.85 0.92 499456
accuracy 0.85 500482
macro avg 0.50 0.73 0.47 500482
weighted avg 1.00 0.85 0.92 500482
Accuracy: 0.8512973493552216
precision recall f1-score support
0 0.01 0.62 0.02 1026
1 1.00 0.85 0.92 499456
accuracy 0.85 500482
macro avg 0.50 0.73 0.47 500482
weighted avg 1.00 0.85 0.92 500482
Accuracy: 0.8512973493552216
LR_2_log_0.01
precision recall f1-score support
0 0.07 0.58 0.13 98473
1 0.99 0.85 0.91 4925407
accuracy 0.84 5023880
macro avg 0.53 0.71 0.52 5023880
weighted avg 0.97 0.84 0.90 5023880
Accuracy: 0.8419739324983877
precision recall f1-score support
0 0.07 0.58 0.13 98473
1 0.99 0.85 0.91 4925407
accuracy 0.84 5023880
macro avg 0.53 0.71 0.52 5023880
weighted avg 0.97 0.84 0.90 5023880
Accuracy: 0.8419739324983877
LR_2_log_0.1
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.7617663951717766
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.7617663951717766
LR_2_log_0.2
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.7436901233768621
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.7436901233768621
LR_2_log_0.4
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.73 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7348725701667393
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.73 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7348725701667393
LR_2_log_All
precision recall f1-score support
0 0.44 0.56 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.62 0.61 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.6468137914791966
precision recall f1-score support
0 0.44 0.56 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.62 0.61 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.6468137914791966
LR_2_mean_0.001
precision recall f1-score support
0 0.01 0.62 0.02 1026
1 1.00 0.85 0.92 499456
accuracy 0.85 500482
macro avg 0.50 0.73 0.47 500482
weighted avg 1.00 0.85 0.92 500482
Accuracy: 0.8513592896447825
precision recall f1-score support
0 0.01 0.62 0.02 1026
1 1.00 0.85 0.92 499456
accuracy 0.85 500482
macro avg 0.50 0.73 0.47 500482
weighted avg 1.00 0.85 0.92 500482
Accuracy: 0.8513592896447825
LR_2_mean_0.01
precision recall f1-score support
0 0.07 0.58 0.13 98473
1 0.99 0.85 0.91 4925407
accuracy 0.84 5023880
macro avg 0.53 0.71 0.52 5023880
weighted avg 0.97 0.84 0.90 5023880
Accuracy: 0.8418714220881072
precision recall f1-score support
0 0.07 0.58 0.13 98473
1 0.99 0.85 0.91 4925407
accuracy 0.84 5023880
macro avg 0.53 0.71 0.52 5023880
weighted avg 0.97 0.84 0.90 5023880
Accuracy: 0.8418714220881072
LR_2_mean_0.1
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.7616650990208654
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.7616650990208654
LR_2_mean_0.2
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.7437538833491875
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.7437538833491875
LR_2_mean_0.4
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.74 169691582
Accuracy: 0.736309158812604
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.74 169691582
Accuracy: 0.736309158812604
LR_2_mean_All
precision recall f1-score support
0 0.39 0.51 0.44 99768080
1 0.75 0.64 0.69 225185809
accuracy 0.60 324953889
macro avg 0.57 0.58 0.57 324953889
weighted avg 0.64 0.60 0.61 324953889
Accuracy: 0.6025098964117952
precision recall f1-score support
0 0.39 0.51 0.44 99768080
1 0.75 0.64 0.69 225185809
accuracy 0.60 324953889
macro avg 0.57 0.58 0.57 324953889
weighted avg 0.64 0.60 0.61 324953889
Accuracy: 0.6025098964117952
LR_3_0.001
precision recall f1-score support
0 0.00 0.72 0.01 1026
1 1.00 0.59 0.74 499456
accuracy 0.59 500482
macro avg 0.50 0.66 0.37 500482
weighted avg 1.00 0.59 0.74 500482
Accuracy: 0.5874157312350894
precision recall f1-score support
0 0.00 0.72 0.01 1026
1 1.00 0.59 0.74 499456
accuracy 0.59 500482
macro avg 0.50 0.66 0.37 500482
weighted avg 1.00 0.59 0.74 500482
Accuracy: 0.5874157312350894
LR_3_0.01
precision recall f1-score support
0 0.04 0.68 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6324360852568135
precision recall f1-score support
0 0.04 0.68 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6324360852568135
LR_3_0.1
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.64 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6420325187544159
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.64 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6420325187544159
LR_3_0.2
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.74 73187446
accuracy 0.66 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.66 0.68 98808073
Accuracy: 0.6570850744149216
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.74 73187446
accuracy 0.66 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.66 0.68 98808073
Accuracy: 0.6570850744149216
LR_3_0.4
precision recall f1-score support
0 0.59 0.72 0.65 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6925212707369303
precision recall f1-score support
0 0.59 0.72 0.65 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6925212707369303
LR_3_All
precision recall f1-score support
0 0.40 0.70 0.51 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.61 0.57 324953889
weighted avg 0.68 0.58 0.60 324953889
Accuracy: 0.5821352179601088
precision recall f1-score support
0 0.40 0.70 0.51 99768080
1 0.80 0.53 0.64 225185809
accuracy 0.58 324953889
macro avg 0.60 0.61 0.57 324953889
weighted avg 0.68 0.58 0.60 324953889
Accuracy: 0.5821352179601088
LR_3_log_0.001
precision recall f1-score support
0 0.01 0.66 0.01 1026
1 1.00 0.75 0.86 499456
accuracy 0.75 500482
macro avg 0.50 0.71 0.43 500482
weighted avg 1.00 0.75 0.86 500482
Accuracy: 0.752214864870265
precision recall f1-score support
0 0.01 0.66 0.01 1026
1 1.00 0.75 0.86 499456
accuracy 0.75 500482
macro avg 0.50 0.71 0.43 500482
weighted avg 1.00 0.75 0.86 500482
Accuracy: 0.752214864870265
LR_3_log_0.01
precision recall f1-score support
0 0.06 0.60 0.11 98473
1 0.99 0.80 0.89 4925407
accuracy 0.80 5023880
macro avg 0.52 0.70 0.50 5023880
weighted avg 0.97 0.80 0.87 5023880
Accuracy: 0.8002306981854662
precision recall f1-score support
0 0.06 0.60 0.11 98473
1 0.99 0.80 0.89 4925407
accuracy 0.80 5023880
macro avg 0.52 0.70 0.50 5023880
weighted avg 0.97 0.80 0.87 5023880
Accuracy: 0.8002306981854662
LR_3_log_0.1
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.760560521338047
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.760560521338047
LR_3_log_0.2
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.743429911845361
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.743429911845361
LR_3_log_0.4
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.73 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7347876926505406
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.73 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7347876926505406
LR_3_log_All
precision recall f1-score support
0 0.44 0.57 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.62 0.61 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.6464200309970748
precision recall f1-score support
0 0.44 0.57 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.62 0.61 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.6464200309970748
LR_3_mean_0.001
precision recall f1-score support
0 0.01 0.66 0.01 1026
1 1.00 0.75 0.86 499456
accuracy 0.75 500482
macro avg 0.50 0.71 0.43 500482
weighted avg 1.00 0.75 0.86 500482
Accuracy: 0.7521888899101267
precision recall f1-score support
0 0.01 0.66 0.01 1026
1 1.00 0.75 0.86 499456
accuracy 0.75 500482
macro avg 0.50 0.71 0.43 500482
weighted avg 1.00 0.75 0.86 500482
Accuracy: 0.7521888899101267
LR_3_mean_0.01
precision recall f1-score support
0 0.06 0.60 0.10 98473
1 0.99 0.80 0.89 4925407
accuracy 0.80 5023880
macro avg 0.52 0.70 0.50 5023880
weighted avg 0.97 0.80 0.87 5023880
Accuracy: 0.7988445185792654
precision recall f1-score support
0 0.06 0.60 0.10 98473
1 0.99 0.80 0.89 4925407
accuracy 0.80 5023880
macro avg 0.52 0.70 0.50 5023880
weighted avg 0.97 0.80 0.87 5023880
Accuracy: 0.7988445185792654
LR_3_mean_0.1
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.7603852803714095
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.7603852803714095
LR_3_mean_0.2
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.7433628626681141
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.7433628626681141
LR_3_mean_0.4
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.74 169691582
Accuracy: 0.7362080047082123
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.74 169691582
Accuracy: 0.7362080047082123
LR_3_mean_All
precision recall f1-score support
0 0.39 0.51 0.44 99768080
1 0.75 0.64 0.69 225185809
accuracy 0.60 324953889
macro avg 0.57 0.58 0.57 324953889
weighted avg 0.64 0.60 0.61 324953889
Accuracy: 0.6018183336774898
precision recall f1-score support
0 0.39 0.51 0.44 99768080
1 0.75 0.64 0.69 225185809
accuracy 0.60 324953889
macro avg 0.57 0.58 0.57 324953889
weighted avg 0.64 0.60 0.61 324953889
Accuracy: 0.6018183336774898
LR_4_0.001
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.6261164237674881
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.6261164237674881
LR_4_0.01
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6311675438107598
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6311675438107598
LR_4_0.1
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.63 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6413143351312566
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.63 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6413143351312566
LR_4_0.2
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.73 73187446
accuracy 0.65 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.65 0.68 98808073
Accuracy: 0.654479912790122
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.73 73187446
accuracy 0.65 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.65 0.68 98808073
Accuracy: 0.654479912790122
LR_4_0.4
precision recall f1-score support
0 0.59 0.71 0.64 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6928726022484721
precision recall f1-score support
0 0.59 0.71 0.64 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6928726022484721
LR_4_All
precision recall f1-score support
0 0.48 0.65 0.55 99768080
1 0.82 0.68 0.74 225185809
accuracy 0.67 324953889
macro avg 0.65 0.67 0.65 324953889
weighted avg 0.71 0.67 0.69 324953889
Accuracy: 0.6742106508532969
precision recall f1-score support
0 0.48 0.65 0.55 99768080
1 0.82 0.68 0.74 225185809
accuracy 0.67 324953889
macro avg 0.65 0.67 0.65 324953889
weighted avg 0.71 0.67 0.69 324953889
Accuracy: 0.6742106508532969
LR_4_log_0.001
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9368828449374803
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9368828449374803
LR_4_log_0.01
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.62 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.9466394499868628
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.62 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.9466394499868628
LR_4_log_0.1
precision recall f1-score support
0 0.40 0.57 0.47 8019514
1 0.91 0.84 0.87 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.67 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.7956631031784255
precision recall f1-score support
0 0.40 0.57 0.47 8019514
1 0.91 0.84 0.87 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.67 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.7956631031784255
LR_4_log_0.2
precision recall f1-score support
0 0.51 0.60 0.56 25620627
1 0.85 0.80 0.83 73187446
accuracy 0.75 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.75 0.76 98808073
Accuracy: 0.7493842836101055
precision recall f1-score support
0 0.51 0.60 0.56 25620627
1 0.85 0.80 0.83 73187446
accuracy 0.75 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.75 0.76 98808073
Accuracy: 0.7493842836101055
LR_4_log_0.4
precision recall f1-score support
0 0.65 0.65 0.65 66028440
1 0.78 0.78 0.78 103663142
accuracy 0.73 169691582
macro avg 0.71 0.71 0.71 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7281720610041811
precision recall f1-score support
0 0.65 0.65 0.65 66028440
1 0.78 0.78 0.78 103663142
accuracy 0.73 169691582
macro avg 0.71 0.71 0.71 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7281720610041811
LR_4_log_All
precision recall f1-score support
0 0.46 0.68 0.55 99768080
1 0.82 0.64 0.72 225185809
accuracy 0.65 324953889
macro avg 0.64 0.66 0.63 324953889
weighted avg 0.71 0.65 0.67 324953889
Accuracy: 0.6533813140485295
precision recall f1-score support
0 0.46 0.68 0.55 99768080
1 0.82 0.64 0.72 225185809
accuracy 0.65 324953889
macro avg 0.64 0.66 0.63 324953889
weighted avg 0.71 0.65 0.67 324953889
Accuracy: 0.6533813140485295
LR_4_mean_0.001
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.75 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9369787524826068
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.75 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9369787524826068
LR_4_mean_0.01
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.62 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.9466388528388416
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.62 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.9466388528388416
LR_4_mean_0.1
precision recall f1-score support
0 0.40 0.57 0.47 8019514
1 0.91 0.84 0.87 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.67 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.7957758660771815
precision recall f1-score support
0 0.40 0.57 0.47 8019514
1 0.91 0.84 0.87 42910358
accuracy 0.80 50929872
macro avg 0.66 0.71 0.67 50929872
weighted avg 0.83 0.80 0.81 50929872
Accuracy: 0.7957758660771815
LR_4_mean_0.2
precision recall f1-score support
0 0.51 0.60 0.55 25620627
1 0.85 0.80 0.83 73187446
accuracy 0.75 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.75 0.76 98808073
Accuracy: 0.7492843727455347
precision recall f1-score support
0 0.51 0.60 0.55 25620627
1 0.85 0.80 0.83 73187446
accuracy 0.75 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.75 0.76 98808073
Accuracy: 0.7492843727455347
LR_4_mean_0.4
precision recall f1-score support
0 0.66 0.65 0.65 66028440
1 0.78 0.79 0.78 103663142
accuracy 0.73 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7314344267236544
precision recall f1-score support
0 0.66 0.65 0.65 66028440
1 0.78 0.79 0.78 103663142
accuracy 0.73 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.73 0.73 169691582
Accuracy: 0.7314344267236544
LR_4_mean_All
precision recall f1-score support
0 0.46 0.69 0.55 99768080
1 0.82 0.65 0.73 225185809
accuracy 0.66 324953889
macro avg 0.64 0.67 0.64 324953889
weighted avg 0.71 0.66 0.67 324953889
Accuracy: 0.6599687655992325
precision recall f1-score support
0 0.46 0.69 0.55 99768080
1 0.82 0.65 0.73 225185809
accuracy 0.66 324953889
macro avg 0.64 0.67 0.64 324953889
weighted avg 0.71 0.66 0.67 324953889
Accuracy: 0.6599687655992325
LR_4_robust_scaler_0.001
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.626168373687765
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.626168373687765
LR_4_robust_scaler_0.01
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6313739579767033
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6313739579767033
LR_4_robust_scaler_0.1
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.63 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6413206968201295
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.63 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6413206968201295
LR_4_robust_scaler_0.2
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.73 73187446
accuracy 0.65 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.65 0.68 98808073
Accuracy: 0.6545591775684159
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.73 73187446
accuracy 0.65 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.65 0.68 98808073
Accuracy: 0.6545591775684159
LR_4_robust_scaler_0.4
precision recall f1-score support
0 0.59 0.71 0.64 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6928880007730731
precision recall f1-score support
0 0.59 0.71 0.64 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6928880007730731
LR_4_robust_scaler_All
precision recall f1-score support
0 0.50 0.63 0.56 99768080
1 0.81 0.72 0.76 225185809
accuracy 0.69 324953889
macro avg 0.66 0.67 0.66 324953889
weighted avg 0.72 0.69 0.70 324953889
Accuracy: 0.6909677268087719
precision recall f1-score support
0 0.50 0.63 0.56 99768080
1 0.81 0.72 0.76 225185809
accuracy 0.69 324953889
macro avg 0.66 0.67 0.66 324953889
weighted avg 0.72 0.69 0.70 324953889
Accuracy: 0.6909677268087719
LR_4_std_scaler_0.001
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.6261903525001898
precision recall f1-score support
0 0.00 0.71 0.01 1026
1 1.00 0.63 0.77 499456
accuracy 0.63 500482
macro avg 0.50 0.67 0.39 500482
weighted avg 1.00 0.63 0.77 500482
Accuracy: 0.6261903525001898
LR_4_std_scaler_0.01
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.631355645437391
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.631355645437391
LR_4_std_scaler_0.1
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.63 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6413164164245297
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.63 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6413164164245297
LR_4_std_scaler_0.2
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.73 73187446
accuracy 0.65 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.65 0.68 98808073
Accuracy: 0.6545269636014458
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.73 73187446
accuracy 0.65 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.65 0.68 98808073
Accuracy: 0.6545269636014458
LR_4_std_scaler_0.4
precision recall f1-score support
0 0.59 0.71 0.64 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.692828039047924
precision recall f1-score support
0 0.59 0.71 0.64 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.692828039047924
LR_4_std_scaler_All
precision recall f1-score support
0 0.50 0.63 0.56 99768080
1 0.81 0.72 0.76 225185809
accuracy 0.69 324953889
macro avg 0.66 0.67 0.66 324953889
weighted avg 0.72 0.69 0.70 324953889
Accuracy: 0.6909617598083277
precision recall f1-score support
0 0.50 0.63 0.56 99768080
1 0.81 0.72 0.76 225185809
accuracy 0.69 324953889
macro avg 0.66 0.67 0.66 324953889
weighted avg 0.72 0.69 0.70 324953889
Accuracy: 0.6909617598083277
LR_5_0.001
precision recall f1-score support
0 0.00 0.72 0.01 1026
1 1.00 0.59 0.74 499456
accuracy 0.59 500482
macro avg 0.50 0.66 0.37 500482
weighted avg 1.00 0.59 0.74 500482
Accuracy: 0.5874337138998006
precision recall f1-score support
0 0.00 0.72 0.01 1026
1 1.00 0.59 0.74 499456
accuracy 0.59 500482
macro avg 0.50 0.66 0.37 500482
weighted avg 1.00 0.59 0.74 500482
Accuracy: 0.5874337138998006
LR_5_0.01
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6316301344777343
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6316301344777343
LR_5_0.1
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.63 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.641262027911635
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.63 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.641262027911635
LR_5_0.2
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.73 73187446
accuracy 0.65 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.65 0.68 98808073
Accuracy: 0.6545023805898937
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.73 73187446
accuracy 0.65 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.65 0.68 98808073
Accuracy: 0.6545023805898937
LR_5_0.4
precision recall f1-score support
0 0.59 0.71 0.64 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6928688955236447
precision recall f1-score support
0 0.59 0.71 0.64 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.6928688955236447
LR_5_All
precision recall f1-score support
0 0.50 0.63 0.56 99768080
1 0.81 0.72 0.76 225185809
accuracy 0.69 324953889
macro avg 0.66 0.67 0.66 324953889
weighted avg 0.72 0.69 0.70 324953889
Accuracy: 0.6910263597429973
precision recall f1-score support
0 0.50 0.63 0.56 99768080
1 0.81 0.72 0.76 225185809
accuracy 0.69 324953889
macro avg 0.66 0.67 0.66 324953889
weighted avg 0.72 0.69 0.70 324953889
Accuracy: 0.6910263597429973
LR_5_imba_0.001
precision recall f1-score support
0 0.00 0.00 0.00 1026
1 1.00 1.00 1.00 499456
accuracy 1.00 500482
macro avg 0.50 0.50 0.50 500482
weighted avg 1.00 1.00 1.00 500482
Accuracy: 0.9979499762229211
precision recall f1-score support
0 0.00 0.00 0.00 1026
1 1.00 1.00 1.00 499456
accuracy 1.00 500482
macro avg 0.50 0.50 0.50 500482
weighted avg 1.00 1.00 1.00 500482
Accuracy: 0.9979499762229211
LR_5_imba_0.01
precision recall f1-score support
0 0.00 0.00 0.00 98473
1 0.98 1.00 0.99 4925407
accuracy 0.98 5023880
macro avg 0.49 0.50 0.50 5023880
weighted avg 0.96 0.98 0.97 5023880
Accuracy: 0.9803990143076666
precision recall f1-score support
0 0.00 0.00 0.00 98473
1 0.98 1.00 0.99 4925407
accuracy 0.98 5023880
macro avg 0.49 0.50 0.50 5023880
weighted avg 0.96 0.98 0.97 5023880
Accuracy: 0.9803990143076666
LR_5_imba_0.1
precision recall f1-score support
0 1.00 0.00 0.00 8019514
1 0.84 1.00 0.91 42910358
accuracy 0.84 50929872
macro avg 0.92 0.50 0.46 50929872
weighted avg 0.87 0.84 0.77 50929872
Accuracy: 0.842538304435558
precision recall f1-score support
0 1.00 0.00 0.00 8019514
1 0.84 1.00 0.91 42910358
accuracy 0.84 50929872
macro avg 0.92 0.50 0.46 50929872
weighted avg 0.87 0.84 0.77 50929872
Accuracy: 0.842538304435558
LR_5_imba_0.2
precision recall f1-score support
0 0.91 0.42 0.58 25620627
1 0.83 0.99 0.90 73187446
accuracy 0.84 98808073
macro avg 0.87 0.70 0.74 98808073
weighted avg 0.85 0.84 0.82 98808073
Accuracy: 0.8393895203279594
precision recall f1-score support
0 0.91 0.42 0.58 25620627
1 0.83 0.99 0.90 73187446
accuracy 0.84 98808073
macro avg 0.87 0.70 0.74 98808073
weighted avg 0.85 0.84 0.82 98808073
Accuracy: 0.8393895203279594
LR_5_imba_0.4
precision recall f1-score support
0 0.69 0.61 0.65 66028440
1 0.77 0.83 0.80 103663142
accuracy 0.74 169691582
macro avg 0.73 0.72 0.72 169691582
weighted avg 0.74 0.74 0.74 169691582
Accuracy: 0.7443111114374548
precision recall f1-score support
0 0.69 0.61 0.65 66028440
1 0.77 0.83 0.80 103663142
accuracy 0.74 169691582
macro avg 0.73 0.72 0.72 169691582
weighted avg 0.74 0.74 0.74 169691582
Accuracy: 0.7443111114374548
LR_5_imba_All
precision recall f1-score support
0 0.73 0.34 0.47 99768080
1 0.76 0.95 0.85 225185809
accuracy 0.76 324953889
macro avg 0.75 0.64 0.66 324953889
weighted avg 0.76 0.76 0.73 324953889
Accuracy: 0.7600015705612928
precision recall f1-score support
0 0.73 0.34 0.47 99768080
1 0.76 0.95 0.85 225185809
accuracy 0.76 324953889
macro avg 0.75 0.64 0.66 324953889
weighted avg 0.76 0.76 0.73 324953889
Accuracy: 0.7600015705612928
LR_6_0.001
precision recall f1-score support
0 0.00 0.72 0.01 1026
1 1.00 0.59 0.74 499456
accuracy 0.59 500482
macro avg 0.50 0.66 0.37 500482
weighted avg 1.00 0.59 0.74 500482
Accuracy: 0.5874357119736574
precision recall f1-score support
0 0.00 0.72 0.01 1026
1 1.00 0.59 0.74 499456
accuracy 0.59 500482
macro avg 0.50 0.66 0.37 500482
weighted avg 1.00 0.59 0.74 500482
Accuracy: 0.5874357119736574
LR_6_0.01
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6318892967188706
precision recall f1-score support
0 0.04 0.69 0.07 98473
1 0.99 0.63 0.77 4925407
accuracy 0.63 5023880
macro avg 0.51 0.66 0.42 5023880
weighted avg 0.97 0.63 0.76 5023880
Accuracy: 0.6318892967188706
LR_6_0.1
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.63 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6413257626094171
precision recall f1-score support
0 0.26 0.68 0.37 8019514
1 0.91 0.63 0.75 42910358
accuracy 0.64 50929872
macro avg 0.59 0.66 0.56 50929872
weighted avg 0.81 0.64 0.69 50929872
Accuracy: 0.6413257626094171
LR_6_0.2
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.73 73187446
accuracy 0.65 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.65 0.68 98808073
Accuracy: 0.6544541962679506
precision recall f1-score support
0 0.40 0.68 0.51 25620627
1 0.85 0.65 0.73 73187446
accuracy 0.65 98808073
macro avg 0.63 0.66 0.62 98808073
weighted avg 0.74 0.65 0.68 98808073
Accuracy: 0.6544541962679506
LR_6_0.4
precision recall f1-score support
0 0.59 0.71 0.64 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.692852742689381
precision recall f1-score support
0 0.59 0.71 0.64 66028440
1 0.79 0.68 0.73 103663142
accuracy 0.69 169691582
macro avg 0.69 0.70 0.69 169691582
weighted avg 0.71 0.69 0.70 169691582
Accuracy: 0.692852742689381
LR_6_All
precision recall f1-score support
0 0.50 0.63 0.56 99768080
1 0.81 0.72 0.76 225185809
accuracy 0.69 324953889
macro avg 0.66 0.67 0.66 324953889
weighted avg 0.72 0.69 0.70 324953889
Accuracy: 0.6910168353147483
precision recall f1-score support
0 0.50 0.63 0.56 99768080
1 0.81 0.72 0.76 225185809
accuracy 0.69 324953889
macro avg 0.66 0.67 0.66 324953889
weighted avg 0.72 0.69 0.70 324953889
Accuracy: 0.6910168353147483
LR_6_imba_0.001
precision recall f1-score support
0 0.00 0.00 0.00 1026
1 1.00 1.00 1.00 499456
accuracy 1.00 500482
macro avg 0.50 0.50 0.50 500482
weighted avg 1.00 1.00 1.00 500482
Accuracy: 0.9979499762229211
precision recall f1-score support
0 0.00 0.00 0.00 1026
1 1.00 1.00 1.00 499456
accuracy 1.00 500482
macro avg 0.50 0.50 0.50 500482
weighted avg 1.00 1.00 1.00 500482
Accuracy: 0.9979499762229211
LR_6_imba_0.01
precision recall f1-score support
0 0.00 0.00 0.00 98473
1 0.98 1.00 0.99 4925407
accuracy 0.98 5023880
macro avg 0.49 0.50 0.50 5023880
weighted avg 0.96 0.98 0.97 5023880
Accuracy: 0.9803990143076666
precision recall f1-score support
0 0.00 0.00 0.00 98473
1 0.98 1.00 0.99 4925407
accuracy 0.98 5023880
macro avg 0.49 0.50 0.50 5023880
weighted avg 0.96 0.98 0.97 5023880
Accuracy: 0.9803990143076666
LR_6_imba_0.1
precision recall f1-score support
0 1.00 0.00 0.00 8019514
1 0.84 1.00 0.91 42910358
accuracy 0.84 50929872
macro avg 0.92 0.50 0.46 50929872
weighted avg 0.87 0.84 0.77 50929872
Accuracy: 0.8425383240704002
precision recall f1-score support
0 1.00 0.00 0.00 8019514
1 0.84 1.00 0.91 42910358
accuracy 0.84 50929872
macro avg 0.92 0.50 0.46 50929872
weighted avg 0.87 0.84 0.77 50929872
Accuracy: 0.8425383240704002
LR_6_imba_0.2
precision recall f1-score support
0 0.91 0.42 0.58 25620627
1 0.83 0.99 0.90 73187446
accuracy 0.84 98808073
macro avg 0.87 0.70 0.74 98808073
weighted avg 0.85 0.84 0.82 98808073
Accuracy: 0.8394588972502277
precision recall f1-score support
0 0.91 0.42 0.58 25620627
1 0.83 0.99 0.90 73187446
accuracy 0.84 98808073
macro avg 0.87 0.70 0.74 98808073
weighted avg 0.85 0.84 0.82 98808073
Accuracy: 0.8394588972502277
LR_6_imba_0.4
precision recall f1-score support
0 0.69 0.61 0.65 66028440
1 0.77 0.83 0.80 103663142
accuracy 0.74 169691582
macro avg 0.73 0.72 0.72 169691582
weighted avg 0.74 0.74 0.74 169691582
Accuracy: 0.7442905447130548
precision recall f1-score support
0 0.69 0.61 0.65 66028440
1 0.77 0.83 0.80 103663142
accuracy 0.74 169691582
macro avg 0.73 0.72 0.72 169691582
weighted avg 0.74 0.74 0.74 169691582
Accuracy: 0.7442905447130548
LR_6_imba_All
precision recall f1-score support
0 0.73 0.34 0.47 99768080
1 0.76 0.95 0.85 225185809
accuracy 0.76 324953889
macro avg 0.75 0.64 0.66 324953889
weighted avg 0.76 0.76 0.73 324953889
Accuracy: 0.7600320795052864
precision recall f1-score support
0 0.73 0.34 0.47 99768080
1 0.76 0.95 0.85 225185809
accuracy 0.76 324953889
macro avg 0.75 0.64 0.66 324953889
weighted avg 0.76 0.76 0.73 324953889
Accuracy: 0.7600320795052864
LR_7_0.001
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9368788487897667
precision recall f1-score support
0 0.02 0.57 0.04 1026
1 1.00 0.94 0.97 499456
accuracy 0.94 500482
macro avg 0.51 0.76 0.50 500482
weighted avg 1.00 0.94 0.97 500482
Accuracy: 0.9368788487897667
LR_7_0.01
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.63 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.9476126022118363
precision recall f1-score support
0 0.19 0.52 0.28 98473
1 0.99 0.96 0.97 4925407
accuracy 0.95 5023880
macro avg 0.59 0.74 0.63 5023880
weighted avg 0.97 0.95 0.96 5023880
Accuracy: 0.9476126022118363
LR_7_0.1
precision recall f1-score support
0 0.38 0.58 0.46 8019514
1 0.91 0.83 0.87 42910358
accuracy 0.79 50929872
macro avg 0.65 0.70 0.66 50929872
weighted avg 0.83 0.79 0.80 50929872
Accuracy: 0.7869018009705581
precision recall f1-score support
0 0.38 0.58 0.46 8019514
1 0.91 0.83 0.87 42910358
accuracy 0.79 50929872
macro avg 0.65 0.70 0.66 50929872
weighted avg 0.83 0.79 0.80 50929872
Accuracy: 0.7869018009705581
LR_7_0.2
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.742507527699685
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.742507527699685
LR_7_0.4
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.73 169691582
Accuracy: 0.7354215956334239
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.73 169691582
Accuracy: 0.7354215956334239
LR_7_All
precision recall f1-score support
0 0.44 0.58 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.63 0.62 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.6482772452678663
precision recall f1-score support
0 0.44 0.58 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.63 0.62 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.6482772452678663
LR_8_0.001
precision recall f1-score support
0 0.01 0.66 0.01 1026
1 1.00 0.75 0.86 499456
accuracy 0.75 500482
macro avg 0.50 0.71 0.43 500482
weighted avg 1.00 0.75 0.86 500482
Accuracy: 0.752214864870265
precision recall f1-score support
0 0.01 0.66 0.01 1026
1 1.00 0.75 0.86 499456
accuracy 0.75 500482
macro avg 0.50 0.71 0.43 500482
weighted avg 1.00 0.75 0.86 500482
Accuracy: 0.752214864870265
LR_8_0.01
precision recall f1-score support
0 0.06 0.60 0.11 98473
1 0.99 0.81 0.89 4925407
accuracy 0.80 5023880
macro avg 0.52 0.70 0.50 5023880
weighted avg 0.97 0.80 0.87 5023880
Accuracy: 0.8023917768736515
precision recall f1-score support
0 0.06 0.60 0.11 98473
1 0.99 0.81 0.89 4925407
accuracy 0.80 5023880
macro avg 0.52 0.70 0.50 5023880
weighted avg 0.97 0.80 0.87 5023880
Accuracy: 0.8023917768736515
LR_8_0.1
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.7604401008508327
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.7604401008508327
LR_8_0.2
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.743415338137401
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.743415338137401
LR_8_0.4
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.74 169691582
Accuracy: 0.7360847575809624
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.74 169691582
Accuracy: 0.7360847575809624
LR_8_All
precision recall f1-score support
0 0.44 0.58 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.63 0.62 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.64812848877768
precision recall f1-score support
0 0.44 0.58 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.63 0.62 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.64812848877768
LR_9_0.001
precision recall f1-score support
0 0.01 0.61 0.02 1026
1 1.00 0.85 0.92 499456
accuracy 0.85 500482
macro avg 0.50 0.73 0.47 500482
weighted avg 1.00 0.85 0.92 500482
Accuracy: 0.8512813647643671
precision recall f1-score support
0 0.01 0.61 0.02 1026
1 1.00 0.85 0.92 499456
accuracy 0.85 500482
macro avg 0.50 0.73 0.47 500482
weighted avg 1.00 0.85 0.92 500482
Accuracy: 0.8512813647643671
LR_9_0.01
precision recall f1-score support
0 0.07 0.58 0.13 98473
1 0.99 0.85 0.91 4925407
accuracy 0.84 5023880
macro avg 0.53 0.71 0.52 5023880
weighted avg 0.97 0.84 0.90 5023880
Accuracy: 0.841862265818451
precision recall f1-score support
0 0.07 0.58 0.13 98473
1 0.99 0.85 0.91 4925407
accuracy 0.84 5023880
macro avg 0.53 0.71 0.52 5023880
weighted avg 0.97 0.84 0.90 5023880
Accuracy: 0.841862265818451
LR_9_0.1
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.7617056449700089
precision recall f1-score support
0 0.35 0.60 0.44 8019514
1 0.91 0.79 0.85 42910358
accuracy 0.76 50929872
macro avg 0.63 0.69 0.64 50929872
weighted avg 0.82 0.76 0.78 50929872
Accuracy: 0.7617056449700089
LR_9_0.2
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.743784457774012
precision recall f1-score support
0 0.50 0.61 0.55 25620627
1 0.85 0.79 0.82 73187446
accuracy 0.74 98808073
macro avg 0.68 0.70 0.69 98808073
weighted avg 0.76 0.74 0.75 98808073
Accuracy: 0.743784457774012
LR_9_0.4
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.74 169691582
Accuracy: 0.7361713499730352
precision recall f1-score support
0 0.67 0.64 0.65 66028440
1 0.78 0.80 0.79 103663142
accuracy 0.74 169691582
macro avg 0.72 0.72 0.72 169691582
weighted avg 0.73 0.74 0.74 169691582
Accuracy: 0.7361713499730352
LR_9_All
precision recall f1-score support
0 0.44 0.58 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.63 0.62 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.6483561333835891
precision recall f1-score support
0 0.44 0.58 0.50 99768080
1 0.78 0.68 0.73 225185809
accuracy 0.65 324953889
macro avg 0.61 0.63 0.62 324953889
weighted avg 0.68 0.65 0.66 324953889
Accuracy: 0.6483561333835891
Model Metrics
True Positives
True Negatives
False Positives
False Negatives
Individual Workload Result
zipf_0_15
0.001
0.01
0.1
0.2
0.4
Ignore Obj Size
0.001
0.01
0.1
0.2
0.4
zipf_0_16
0.001
0.01
0.1
0.2
0.4
Ignore Obj Size
0.001
0.01
0.1
0.2
0.4
zipf_0_17
0.001
0.01
0.1
0.2
0.4
Ignore Obj Size
0.001
0.01
0.1
0.2
0.4
zipf_0_18
0.001
0.01
0.1
0.2
0.4
Ignore Obj Size
0.001
0.01
0.1
0.2
0.4
zipf_0_19
0.001
0.01
0.1
0.2
0.4
Ignore Obj Size
0.001
0.01
0.1
0.2
0.4